The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world's most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. About the Data Platform Team Our Data Platform team is the engineering backbone of Tripadvisor's data ecosystem. Formed from the core fundamentals of our Data Engineering and Software Engineering (Data Platform) groups, this unified team combines deep data pipeline expertise with robust platform engineering capabilities. We are responsible for providing software and infrastructure that enable Tripadvisor to better understand visitor preferences, power experimentation across all surfaces (website, mobile app, and customer communications), and drive GenAI, Analytical, and DSML initiatives at petabyte scale. Our team builds and maintains: Streaming and batch data platforms that unlock data across Tripadvisor ETL pipelines and data models serving terabytes and growing datasets in Snowflake, BigQuery, and Hive, Orchestration, scheduling, and ETL generation tools to support cloud migrations and petabyte-scale operations, Tracking instrumentation, information architecture, and data governance tooling for business-critical analytics. We collaborate closely with Product, Analytics, Data Science, CRM, Marketing, Finance, and Machine Learning teams across Tripadvisor's global engineering organization. Tripadvisor is looking for a Data Engineer II to join our fast-moving Data Platform group. In this role, you will design, build, and sustain the data infrastructure that powers the world's most trusted travel platform. You'll bring both strong software engineering fundamentals and hands on data engineering expertise - writing production-quality Java and Python, architecting reliable pipelines, and delivering end-to-end solutions that scale to hundreds of millions of travelers. Do you enjoy building features end-to-end? Do you thrive working with a broad technology stack, releasing frequently, and collaborating with talented engineers worldwide? If so, we'd love to talk. What You'll Do Data Engineering & Data Products, ETLs Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms. Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization. Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. Ensure enterprise data integrity, validation, documentation, and governance. Platform & Software Engineering Write production Java and Python code across our evolving platform stack - from data ingestion and event processing to REST services and internal tooling. Build and maintain streaming and batch processing systems (Flink, Spark, Kafka) that power real time and analytical workloads. Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days). Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling. Quality, Collaboration & Ownership Take on projects with independence and a mandate to leave things better than you found them. Be integral to code quality on your team through leadership in design and code review. Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high quality solutions. Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions. Work alongside engineering groups located around the world in a fast paced, dynamic environment. Skills & Experience 4-5+ years of data engineering or general software development experience in a commercial setting. Strong hands on proficiency in both Java and Python for production systems. Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production. Proficiency in SQL and data exploration across large, complex datasets. Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte-scale or larger datasets. Solid foundation in data structures, algorithms, and object oriented design. Professional experience building REST services and working with event queue systems. Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers. Systems performance and tuning experience, with an understanding of how architecture impacts scalability. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Strong analytical skills; desire to write clean, correct, and efficient code. Self paced, organized, and detail oriented with a strong sense of ownership, urgency, and pride in your work. Ability to break down complex problems into simple, pragmatic solutions. Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems. Willingness and ability to take on new technologies as our stack evolves. Nice to Have Experience with stream processing frameworks such as Flink or Spark Streaming. Experience with task orchestration tools such as Apache Airflow or similar systems. Familiarity with additional technologies: GraphQL, React, HTML5, JavaScript, CSS, Postgres, Gradle, BERT. Experience working with and designing infrastructures for large scale data processing (Hive, Snowflake, NoSQL databases). Experience with data governance practices and tooling. Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively. Experience developing scalable code for high volume, low latency systems. What We Offer Competitive compensation packages , including base salary, annual bonus, and more. "Work your way" with flexibility to suit your lifestyle. We take a remote-friendly approach to collaboration, with the option to join on site as often as you'd like in select locations. Flexible schedule . Work life balance is ingrained in our culture by design. Trust and accountability make it work. Donation matching . Give back? Give more! We match qualifying charitable donations annually. Tuition assistance . Want to level up your career? We love to hear it! Receive annual support for qualified programs. Lifestyle benefit . An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you. Travel perks . We believe that travel is employee development, so we provide discounts and more. Employee assistance program . We're here for you with resources and programs to help you through life's challenges. Health benefits . We offer great coverage and competitive premiums. Generous referral scheme . Help us grow and be rewarded with generous awards for referring successful candidates. Our Cultural Pillars Traveller first: We exist to create value for our customer, the traveler. We enable our suppliers and partners to unlock this value. Their collective behaviors and insights are what drives us. Execution is our edge: We act fast, experiment, learn from failure, iterate, and improve the solutions of tomorrow across every aspect of our business. Our execution is agile, data driven, prioritised, and built to scale. We assume no problem is someone else's problem and finish what can be done today, knowing tomorrow will bring fresh challenges. We succeed together: The best outcomes are driven by empathic, humble, and diverse subject matter experts working toward shared goals. We collaborate relentlessly, challenge assumptions, give actionable feedback, and set each other up for success through empowered teams with a clear charter. We transparently take ownership of our growth, individually and as a team. We celebrate the quality of our effort, our learnings, and our collective achievements. Discover more in our Tech Blog , for an inside look into some of our exciting and ground breaking technical projects here at Tripadvisor Group. Tripadvisor Group champions the unique identities, abilities, and experiences of all our people - employees, customers, and partners. This stems from our belief in the transformative power of travel, dining, and experiences to connect us and open doors to worlds very different from our own. Our ED&I strategy shapes how we approach our people, culture, business, and reputation. Tripadvisor Group strives to embed inclusion and belonging across all our brands. We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at . If you have any additional questions about careers at Tripadvisor you can email us at . We have all the answers!
26/07/2026
Full time
The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world's most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. About the Data Platform Team Our Data Platform team is the engineering backbone of Tripadvisor's data ecosystem. Formed from the core fundamentals of our Data Engineering and Software Engineering (Data Platform) groups, this unified team combines deep data pipeline expertise with robust platform engineering capabilities. We are responsible for providing software and infrastructure that enable Tripadvisor to better understand visitor preferences, power experimentation across all surfaces (website, mobile app, and customer communications), and drive GenAI, Analytical, and DSML initiatives at petabyte scale. Our team builds and maintains: Streaming and batch data platforms that unlock data across Tripadvisor ETL pipelines and data models serving terabytes and growing datasets in Snowflake, BigQuery, and Hive, Orchestration, scheduling, and ETL generation tools to support cloud migrations and petabyte-scale operations, Tracking instrumentation, information architecture, and data governance tooling for business-critical analytics. We collaborate closely with Product, Analytics, Data Science, CRM, Marketing, Finance, and Machine Learning teams across Tripadvisor's global engineering organization. Tripadvisor is looking for a Data Engineer II to join our fast-moving Data Platform group. In this role, you will design, build, and sustain the data infrastructure that powers the world's most trusted travel platform. You'll bring both strong software engineering fundamentals and hands on data engineering expertise - writing production-quality Java and Python, architecting reliable pipelines, and delivering end-to-end solutions that scale to hundreds of millions of travelers. Do you enjoy building features end-to-end? Do you thrive working with a broad technology stack, releasing frequently, and collaborating with talented engineers worldwide? If so, we'd love to talk. What You'll Do Data Engineering & Data Products, ETLs Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms. Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization. Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. Ensure enterprise data integrity, validation, documentation, and governance. Platform & Software Engineering Write production Java and Python code across our evolving platform stack - from data ingestion and event processing to REST services and internal tooling. Build and maintain streaming and batch processing systems (Flink, Spark, Kafka) that power real time and analytical workloads. Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days). Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling. Quality, Collaboration & Ownership Take on projects with independence and a mandate to leave things better than you found them. Be integral to code quality on your team through leadership in design and code review. Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high quality solutions. Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions. Work alongside engineering groups located around the world in a fast paced, dynamic environment. Skills & Experience 4-5+ years of data engineering or general software development experience in a commercial setting. Strong hands on proficiency in both Java and Python for production systems. Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production. Proficiency in SQL and data exploration across large, complex datasets. Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte-scale or larger datasets. Solid foundation in data structures, algorithms, and object oriented design. Professional experience building REST services and working with event queue systems. Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers. Systems performance and tuning experience, with an understanding of how architecture impacts scalability. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Strong analytical skills; desire to write clean, correct, and efficient code. Self paced, organized, and detail oriented with a strong sense of ownership, urgency, and pride in your work. Ability to break down complex problems into simple, pragmatic solutions. Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems. Willingness and ability to take on new technologies as our stack evolves. Nice to Have Experience with stream processing frameworks such as Flink or Spark Streaming. Experience with task orchestration tools such as Apache Airflow or similar systems. Familiarity with additional technologies: GraphQL, React, HTML5, JavaScript, CSS, Postgres, Gradle, BERT. Experience working with and designing infrastructures for large scale data processing (Hive, Snowflake, NoSQL databases). Experience with data governance practices and tooling. Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively. Experience developing scalable code for high volume, low latency systems. What We Offer Competitive compensation packages , including base salary, annual bonus, and more. "Work your way" with flexibility to suit your lifestyle. We take a remote-friendly approach to collaboration, with the option to join on site as often as you'd like in select locations. Flexible schedule . Work life balance is ingrained in our culture by design. Trust and accountability make it work. Donation matching . Give back? Give more! We match qualifying charitable donations annually. Tuition assistance . Want to level up your career? We love to hear it! Receive annual support for qualified programs. Lifestyle benefit . An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you. Travel perks . We believe that travel is employee development, so we provide discounts and more. Employee assistance program . We're here for you with resources and programs to help you through life's challenges. Health benefits . We offer great coverage and competitive premiums. Generous referral scheme . Help us grow and be rewarded with generous awards for referring successful candidates. Our Cultural Pillars Traveller first: We exist to create value for our customer, the traveler. We enable our suppliers and partners to unlock this value. Their collective behaviors and insights are what drives us. Execution is our edge: We act fast, experiment, learn from failure, iterate, and improve the solutions of tomorrow across every aspect of our business. Our execution is agile, data driven, prioritised, and built to scale. We assume no problem is someone else's problem and finish what can be done today, knowing tomorrow will bring fresh challenges. We succeed together: The best outcomes are driven by empathic, humble, and diverse subject matter experts working toward shared goals. We collaborate relentlessly, challenge assumptions, give actionable feedback, and set each other up for success through empowered teams with a clear charter. We transparently take ownership of our growth, individually and as a team. We celebrate the quality of our effort, our learnings, and our collective achievements. Discover more in our Tech Blog , for an inside look into some of our exciting and ground breaking technical projects here at Tripadvisor Group. Tripadvisor Group champions the unique identities, abilities, and experiences of all our people - employees, customers, and partners. This stems from our belief in the transformative power of travel, dining, and experiences to connect us and open doors to worlds very different from our own. Our ED&I strategy shapes how we approach our people, culture, business, and reputation. Tripadvisor Group strives to embed inclusion and belonging across all our brands. We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at . If you have any additional questions about careers at Tripadvisor you can email us at . We have all the answers!
Oxford, Oxfordshire, United Kingdom (Hybrid or Remote) The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world's most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. About the Data Platform Team Our Data Platform team is the engineering backbone of Tripadvisor's data ecosystem. Formed from the core fundamentals of our Data Engineering and Software Engineering (Data Platform) groups, this unified team combines deep data pipeline expertise with robust platform engineering capabilities. We are responsible for providing software and infrastructure that enable Tripadvisor to better understand visitor preferences, power experimentation across all surfaces (website, mobile app, and customer communications), and drive GenAI, Analytical, and DSML initiatives at petabyte scale. Our team builds and maintains: Streaming and batch data platforms that unlock data across Tripadvisor ETL pipelines and data models serving terabytes and growing datasets in Snowflake, BigQuery, and Hive Orchestration, scheduling, and ETL generation tools to support cloud migrations and petabyte-scale operations Tracking instrumentation, information architecture, and data governance tooling for business-critical analytics We collaborate closely with Product, Analytics, Data Science, CRM, Marketing, Finance, and Machine Learning teams across Tripadvisor's global engineering organization. Tripadvisor is looking for a Data Engineer II to join our fast-moving Data Platform group. In this role, you will design, build, and sustain the data infrastructure that powers the world's most trusted travel platform. You'll bring both strong software engineering fundamentals and hands on data engineering expertise - writing production-quality Java and Python, architecting reliable pipelines, and delivering end-to-end solutions that scale to hundreds of millions of travelers. Do you enjoy building features end-to-end? Do you thrive working with a broad technology stack, releasing frequently, and collaborating with talented engineers worldwide? If so, we'd love to talk. What You'll Do Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms. Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization. Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. Ensure enterprise data integrity, validation, documentation, and governance. Platform & Software Engineering Write production Java and Python code across our evolving platform stack - from data ingestion and event processing to REST services and internal tooling. Build and maintain streaming and batch processing systems (Flink, Spark, Kafka) that power real time and analytical workloads. Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days). Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling. Take on projects with independence and a mandate to leave things better than you found them. Be integral to code quality on your team through leadership in design and code review. Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high-quality solutions. Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions. Work alongside engineering groups located around the world in a fast paced, dynamic environment. Skills & Experience 4-5+ years of data engineering or general software development experience in a commercial setting. Strong hands on proficiency in both Java and Python for production systems. Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production. Proficiency in SQL and data exploration across large, complex datasets. Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte scale or larger datasets. Solid foundation in data structures, algorithms, and object oriented design. Professional experience building REST services and working with event queue systems. Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers. Systems performance and tuning experience, with an understanding of how architecture impacts scalability. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Strong analytical skills; desire to write clean, correct, and efficient code. Self paced, organized, and detail oriented with a strong sense of ownership, urgency, and pride in your work. Ability to break down complex problems into simple, pragmatic solutions. Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems. Willingness and ability to take on new technologies as our stack evolves. Nice to Have Experience with stream processing frameworks such as Flink or Spark Streaming. Experience with task orchestration tools such as Apache Airflow or similar systems. Experience working with and designing infrastructures for large scale data processing (Hive, Snowflake, NoSQL databases). Experience with data governance practices and tooling. Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively. Experience developing scalable code for high volume, low latency systems. What We Offer Competitive compensation packages, including base salary, annual bonus, and more. "Work your way" with flexibility to suit your lifestyle. We take a remote friendly approach to collaboration, with the option to join on site as often as you'd like in select locations. Flexible schedule. Work life balance is ingrained in our culture by design. Trust and accountability make it work. Donation matching. Give back? Give more! We match qualifying charitable donations annually. Tuition assistance. Want to level up your career? We love to hear it! Receive annual support for qualified programs. Lifestyle benefit. An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you. Travel perks. We believe that travel is employee development, so we provide discounts and more. Employee assistance program. We're here for you with resources and programs to help you through life's challenges. Health benefits. We offer great coverage and competitive premiums. Generous referral scheme. Help us grow and be rewarded with generous awards for referring successful candidates. Traveller first: We exist to create value for our customer, the traveler. We enable our suppliers and partners to unlock this value. Their collective behaviors and insights are what drives us. Execution is our edge: We act fast, experiment, learn from failure, iterate, and improve the solutions of tomorrow across every aspect of our business. Our execution is agile, data driven, prioritised, and built to scale. We assume no problem is someone else's problem and finish what can be done today, knowing tomorrow will bring fresh challenges. We succeed together: The best outcomes are driven by empathic, humble, and diverse subject matter experts working toward shared goals. We collaborate relentlessly, challenge assumptions, give actionable feedback, and set each other up for success through empowered teams with a clear charter. We transparently take ownership of our growth, individually and as a team. We celebrate the quality of our effort, our learnings, and our collective achievements. Discover more in ourTech Blog , for an inside look into some of our exciting and ground breaking technical projects here at Tripadvisor Group. Tripadvisor Group champions the unique identities, abilities, and experiences of all our people - employees, customers, and partners. This stems from our belief in the transformative power of travel, dining, and experiences to connect us and open doors to worlds very different from our own. Our ED&I strategy shapes how we approach our people, culture, business, and reputation. Tripadvisor Group strives to embed inclusion and belonging across all our brands. We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at . If you have any additional questions about careers at Tripadvisor you can email us at . click apply for full job details
26/07/2026
Full time
Oxford, Oxfordshire, United Kingdom (Hybrid or Remote) The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world's most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. About the Data Platform Team Our Data Platform team is the engineering backbone of Tripadvisor's data ecosystem. Formed from the core fundamentals of our Data Engineering and Software Engineering (Data Platform) groups, this unified team combines deep data pipeline expertise with robust platform engineering capabilities. We are responsible for providing software and infrastructure that enable Tripadvisor to better understand visitor preferences, power experimentation across all surfaces (website, mobile app, and customer communications), and drive GenAI, Analytical, and DSML initiatives at petabyte scale. Our team builds and maintains: Streaming and batch data platforms that unlock data across Tripadvisor ETL pipelines and data models serving terabytes and growing datasets in Snowflake, BigQuery, and Hive Orchestration, scheduling, and ETL generation tools to support cloud migrations and petabyte-scale operations Tracking instrumentation, information architecture, and data governance tooling for business-critical analytics We collaborate closely with Product, Analytics, Data Science, CRM, Marketing, Finance, and Machine Learning teams across Tripadvisor's global engineering organization. Tripadvisor is looking for a Data Engineer II to join our fast-moving Data Platform group. In this role, you will design, build, and sustain the data infrastructure that powers the world's most trusted travel platform. You'll bring both strong software engineering fundamentals and hands on data engineering expertise - writing production-quality Java and Python, architecting reliable pipelines, and delivering end-to-end solutions that scale to hundreds of millions of travelers. Do you enjoy building features end-to-end? Do you thrive working with a broad technology stack, releasing frequently, and collaborating with talented engineers worldwide? If so, we'd love to talk. What You'll Do Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms. Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization. Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. Ensure enterprise data integrity, validation, documentation, and governance. Platform & Software Engineering Write production Java and Python code across our evolving platform stack - from data ingestion and event processing to REST services and internal tooling. Build and maintain streaming and batch processing systems (Flink, Spark, Kafka) that power real time and analytical workloads. Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days). Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling. Take on projects with independence and a mandate to leave things better than you found them. Be integral to code quality on your team through leadership in design and code review. Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high-quality solutions. Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions. Work alongside engineering groups located around the world in a fast paced, dynamic environment. Skills & Experience 4-5+ years of data engineering or general software development experience in a commercial setting. Strong hands on proficiency in both Java and Python for production systems. Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production. Proficiency in SQL and data exploration across large, complex datasets. Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte scale or larger datasets. Solid foundation in data structures, algorithms, and object oriented design. Professional experience building REST services and working with event queue systems. Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers. Systems performance and tuning experience, with an understanding of how architecture impacts scalability. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Strong analytical skills; desire to write clean, correct, and efficient code. Self paced, organized, and detail oriented with a strong sense of ownership, urgency, and pride in your work. Ability to break down complex problems into simple, pragmatic solutions. Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems. Willingness and ability to take on new technologies as our stack evolves. Nice to Have Experience with stream processing frameworks such as Flink or Spark Streaming. Experience with task orchestration tools such as Apache Airflow or similar systems. Experience working with and designing infrastructures for large scale data processing (Hive, Snowflake, NoSQL databases). Experience with data governance practices and tooling. Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively. Experience developing scalable code for high volume, low latency systems. What We Offer Competitive compensation packages, including base salary, annual bonus, and more. "Work your way" with flexibility to suit your lifestyle. We take a remote friendly approach to collaboration, with the option to join on site as often as you'd like in select locations. Flexible schedule. Work life balance is ingrained in our culture by design. Trust and accountability make it work. Donation matching. Give back? Give more! We match qualifying charitable donations annually. Tuition assistance. Want to level up your career? We love to hear it! Receive annual support for qualified programs. Lifestyle benefit. An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you. Travel perks. We believe that travel is employee development, so we provide discounts and more. Employee assistance program. We're here for you with resources and programs to help you through life's challenges. Health benefits. We offer great coverage and competitive premiums. Generous referral scheme. Help us grow and be rewarded with generous awards for referring successful candidates. Traveller first: We exist to create value for our customer, the traveler. We enable our suppliers and partners to unlock this value. Their collective behaviors and insights are what drives us. Execution is our edge: We act fast, experiment, learn from failure, iterate, and improve the solutions of tomorrow across every aspect of our business. Our execution is agile, data driven, prioritised, and built to scale. We assume no problem is someone else's problem and finish what can be done today, knowing tomorrow will bring fresh challenges. We succeed together: The best outcomes are driven by empathic, humble, and diverse subject matter experts working toward shared goals. We collaborate relentlessly, challenge assumptions, give actionable feedback, and set each other up for success through empowered teams with a clear charter. We transparently take ownership of our growth, individually and as a team. We celebrate the quality of our effort, our learnings, and our collective achievements. Discover more in ourTech Blog , for an inside look into some of our exciting and ground breaking technical projects here at Tripadvisor Group. Tripadvisor Group champions the unique identities, abilities, and experiences of all our people - employees, customers, and partners. This stems from our belief in the transformative power of travel, dining, and experiences to connect us and open doors to worlds very different from our own. Our ED&I strategy shapes how we approach our people, culture, business, and reputation. Tripadvisor Group strives to embed inclusion and belonging across all our brands. We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at . If you have any additional questions about careers at Tripadvisor you can email us at . click apply for full job details
# Data Engineer at N Consulting LtdJob Title: Data Engineer Location: Glasgow, UK. Job Type: Contract -2 Days onsite. Required Skills & Experience 5+ years of experience as a Data Engineer. Strong expertise in SQL and Python/Scala. Hands-on experience with ETL tools and frameworks. Experience with data warehousing concepts and dimensional modeling. Strong experience in cloud platforms such as AWS / Azure / GCP. Experience with big data technologies (Spark, Hadoop, Kafka). Knowledge of API integrations and microservices-based data ingestion. Experience working in Agile/Scrum environments. Banking Domain Experience (Mandatory) Experience working with banking datasets such as: Payments & Transactions Retail/Corporate Banking Risk & Compliance AML/KYC reporting Regulatory reporting Understanding of financial data governance and audit requirements. Preferred Qualifications Experience with Snowflake, Databricks, or Redshift. Knowledge of data governance tools. Exposure to real-time streaming platforms. Banking domain experience Education Bachelor's or Master's degree in Computer Science, Engineering, or related field.
25/07/2026
Full time
# Data Engineer at N Consulting LtdJob Title: Data Engineer Location: Glasgow, UK. Job Type: Contract -2 Days onsite. Required Skills & Experience 5+ years of experience as a Data Engineer. Strong expertise in SQL and Python/Scala. Hands-on experience with ETL tools and frameworks. Experience with data warehousing concepts and dimensional modeling. Strong experience in cloud platforms such as AWS / Azure / GCP. Experience with big data technologies (Spark, Hadoop, Kafka). Knowledge of API integrations and microservices-based data ingestion. Experience working in Agile/Scrum environments. Banking Domain Experience (Mandatory) Experience working with banking datasets such as: Payments & Transactions Retail/Corporate Banking Risk & Compliance AML/KYC reporting Regulatory reporting Understanding of financial data governance and audit requirements. Preferred Qualifications Experience with Snowflake, Databricks, or Redshift. Knowledge of data governance tools. Exposure to real-time streaming platforms. Banking domain experience Education Bachelor's or Master's degree in Computer Science, Engineering, or related field.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low ego individuals who thrive in dynamic and fast moving environments and move with an experimental mindset - who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Solution Engineer dedicated to one of Snowflake's most strategically important financial services customers. This is a named account role: your entire focus will be a single global financial institution across capital markets, banking, insurance, or asset management. You will own the full technical relationship, drive use case expansion across business units, and act as the go-to trusted advisor to CTO, CDO, and engineering leadership within the account. This is a senior level, high visibility role with global scope and direct exposure to Snowflake's leadership. AS A SENIOR SOLUTION ENGINEER AT SNOWFLAKE, YOU WILL: Own the end-to-end technical relationship for a single strategic Global Account in financial services, from discovery and technical qualification through proof of concept, technical close, and ongoing expansion. Build and deliver compelling demonstrations, solution architectures, and executive presentations that connect Snowflake's platform capabilities to the specific data and AI priorities of financial services buyers. Design and lead proof of concept engagements covering risk analytics, regulatory data platforms, real-time fraud detection, customer intelligence, and AI/ML workloads in FSI environments. Act as a subject matter expert on financial services data architecture, translating complex regulatory and technical requirements into practical, production-ready Snowflake solutions. Partner closely with the Account Executive and leadership as the sole technical owner of the account, co developing the joint success plan and ensuring technical alignment across every active opportunity. Serve as the primary internal advocate for the account within Snowflake, coordinating across Product, Professional Services, Support, and Engineering to resolve blockers and accelerate adoption. Mentor and support junior Solution Engineers on the team, elevating the technical standard of the global accounts practice. OUR IDEAL SENIOR SOLUTION ENGINEER WILL HAVE: 8+ years of experience in pre sales solution engineering, technical consulting, or data engineering in enterprise B2B technology, with significant exposure to financial services customers. Deep understanding of financial services data use cases including risk management, regulatory reporting (Basel, MiFIDII, GDPR), market data, fraud analytics, and AI/ML for credit and customer intelligence. Strong hands on expertise with cloud data platforms, ideally including Snowflake, and the ability to architect and demo enterprise grade solutions live. Proficiency in SQL, Python, and data engineering tools commonly used in FSI environments (dbt, Spark, Kafka, or equivalent). Excellent executive communication skills with the ability to engage credibly with CDOs, CTOs, and CIOs at global financial institutions. Track record of leading complex technical evaluations, winning competitive PoCs, and building lasting technical relationships with strategic enterprise accounts. Experience using AI and LLM based tools in technical workflows, with the ability to articulate Snowflake's Cortex AI capabilities in an FSI context. BONUS POINTS FOR THE FOLLOWING: Direct experience working within or selling to capital markets firms, tier 1 banks, insurers, or global asset managers. Hands on experience with Snowflake including Cortex AI, data sharing, Snowpark, and Native Apps. Familiarity with financial services cloud migration patterns and the technical landscape of legacy platforms (Teradata, Oracle, Hadoop). Experience with real time data architectures, streaming ingestion, and event driven data platforms in regulated environments. Background in data mesh, data product design, or enterprise data governance frameworks relevant to FSI compliance requirements. Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information:
23/07/2026
Full time
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low ego individuals who thrive in dynamic and fast moving environments and move with an experimental mindset - who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Solution Engineer dedicated to one of Snowflake's most strategically important financial services customers. This is a named account role: your entire focus will be a single global financial institution across capital markets, banking, insurance, or asset management. You will own the full technical relationship, drive use case expansion across business units, and act as the go-to trusted advisor to CTO, CDO, and engineering leadership within the account. This is a senior level, high visibility role with global scope and direct exposure to Snowflake's leadership. AS A SENIOR SOLUTION ENGINEER AT SNOWFLAKE, YOU WILL: Own the end-to-end technical relationship for a single strategic Global Account in financial services, from discovery and technical qualification through proof of concept, technical close, and ongoing expansion. Build and deliver compelling demonstrations, solution architectures, and executive presentations that connect Snowflake's platform capabilities to the specific data and AI priorities of financial services buyers. Design and lead proof of concept engagements covering risk analytics, regulatory data platforms, real-time fraud detection, customer intelligence, and AI/ML workloads in FSI environments. Act as a subject matter expert on financial services data architecture, translating complex regulatory and technical requirements into practical, production-ready Snowflake solutions. Partner closely with the Account Executive and leadership as the sole technical owner of the account, co developing the joint success plan and ensuring technical alignment across every active opportunity. Serve as the primary internal advocate for the account within Snowflake, coordinating across Product, Professional Services, Support, and Engineering to resolve blockers and accelerate adoption. Mentor and support junior Solution Engineers on the team, elevating the technical standard of the global accounts practice. OUR IDEAL SENIOR SOLUTION ENGINEER WILL HAVE: 8+ years of experience in pre sales solution engineering, technical consulting, or data engineering in enterprise B2B technology, with significant exposure to financial services customers. Deep understanding of financial services data use cases including risk management, regulatory reporting (Basel, MiFIDII, GDPR), market data, fraud analytics, and AI/ML for credit and customer intelligence. Strong hands on expertise with cloud data platforms, ideally including Snowflake, and the ability to architect and demo enterprise grade solutions live. Proficiency in SQL, Python, and data engineering tools commonly used in FSI environments (dbt, Spark, Kafka, or equivalent). Excellent executive communication skills with the ability to engage credibly with CDOs, CTOs, and CIOs at global financial institutions. Track record of leading complex technical evaluations, winning competitive PoCs, and building lasting technical relationships with strategic enterprise accounts. Experience using AI and LLM based tools in technical workflows, with the ability to articulate Snowflake's Cortex AI capabilities in an FSI context. BONUS POINTS FOR THE FOLLOWING: Direct experience working within or selling to capital markets firms, tier 1 banks, insurers, or global asset managers. Hands on experience with Snowflake including Cortex AI, data sharing, Snowpark, and Native Apps. Familiarity with financial services cloud migration patterns and the technical landscape of legacy platforms (Teradata, Oracle, Hadoop). Experience with real time data architectures, streaming ingestion, and event driven data platforms in regulated environments. Background in data mesh, data product design, or enterprise data governance frameworks relevant to FSI compliance requirements. Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information:
Key Responsibilities: Design our scalable, secure and cost-effective cloud hybrid data solution aligned with Omnia enterprise architecture and Army training objectives. Design innovative data models and metadata systems to interpret and enhance business needs, promoting data as a strategic asset. Develop transitional data architectures and road maps in alignment with Omnia digital transformation objectives, enabling the evolution of integrated training solutions. Collaborate with cross-functional teams and partners to ensure data architectural integrity and alignment. Translate complex technical concepts for a non-technical audience, fostering understanding and buy-in from stakeholders. Support horizon scanning to identify and assess emerging technologies and determine their potential impact on leveraging data analytics to improve training delivery. Membership and contribution to the Omnia Architecture Board(s) to review, define, refine and uphold data architectural principles, policies, and standards across Omnia Training. Work with engineering teams to support and guide the implementation of a variety of solutions across multiple domains, in an agile environment. Manage and lead prototyping and research activity as required to realise the best solutions. Provide oversight and advice to engineers undertaking the design of data models and support the management of data dictionaries. Ensure the security and compliance of data environments through the implementation of appropriate architecture principles, security controls and governance frameworks. Author, review and contribute to technical documentation. Produce High- and low-level design artifacts for data storage, processing, and retrieval systems. Stay current with data technologies, making recommendations for use based on business value. Drive the adoption of these technologies. Serve as the Subject Matter Expert (SME) for the Omnia Data Lakehouse, providing strategic guidance, technical oversight, and deep expertise in its architecture, implementation, and optimisation. Who we are looking for: The Data Architect will provide strategic and practical leadership across the data architecture landscape of the Army Collective Training Service (ACTS). This role is pivotal in shaping and governing the enterprise data architecture to ensure it aligns with the ACTS vision and supports data as a mission-critical asset. Working closely with the Data Lead, Enterprise Architect and Chief Engineer, you will design, evolve, and maintain a secure, scalable, and interoperable data architecture, leveraging cloud services from AWS, Azure, and OCP where appropriate. This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Essential Skills and Experience: Proven experience designing and implementing scalable, secure, and interoperable data architectures in complex environments with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services including use of services like S3, Lambda, Glue, Data Factory, etc. Experience designing and supporting implementation of large-scale data pipelines, data warehousing and Lakehouse technologies. Strong skills in conceptual, logical, and physical data modelling using tools like ER/Studio, ERwin, or Sparx EA (preferred). Experience reverse engineering models from existing databases. Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Experience with API management and gateway tools and services. Experience of RESTful APIs for ingesting and exposing data. Proven track record with data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex work in a rapidly changing environment. Strong critical thinker with problem solving aptitude. A working knowledge of MoD or Government IT Security environments and requirements at various classifications. Desirable Skills and Experience: Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift). Exposure to infrastructure-as-code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Relevant Data and Architecture certification such as TOGAF, MODAF, AWS/Azure Certified Data Architect or Solutions Architect, DAMA Certified Data Management Professional (CDMP) JBRP1_UKTJ
23/07/2026
Full time
Key Responsibilities: Design our scalable, secure and cost-effective cloud hybrid data solution aligned with Omnia enterprise architecture and Army training objectives. Design innovative data models and metadata systems to interpret and enhance business needs, promoting data as a strategic asset. Develop transitional data architectures and road maps in alignment with Omnia digital transformation objectives, enabling the evolution of integrated training solutions. Collaborate with cross-functional teams and partners to ensure data architectural integrity and alignment. Translate complex technical concepts for a non-technical audience, fostering understanding and buy-in from stakeholders. Support horizon scanning to identify and assess emerging technologies and determine their potential impact on leveraging data analytics to improve training delivery. Membership and contribution to the Omnia Architecture Board(s) to review, define, refine and uphold data architectural principles, policies, and standards across Omnia Training. Work with engineering teams to support and guide the implementation of a variety of solutions across multiple domains, in an agile environment. Manage and lead prototyping and research activity as required to realise the best solutions. Provide oversight and advice to engineers undertaking the design of data models and support the management of data dictionaries. Ensure the security and compliance of data environments through the implementation of appropriate architecture principles, security controls and governance frameworks. Author, review and contribute to technical documentation. Produce High- and low-level design artifacts for data storage, processing, and retrieval systems. Stay current with data technologies, making recommendations for use based on business value. Drive the adoption of these technologies. Serve as the Subject Matter Expert (SME) for the Omnia Data Lakehouse, providing strategic guidance, technical oversight, and deep expertise in its architecture, implementation, and optimisation. Who we are looking for: The Data Architect will provide strategic and practical leadership across the data architecture landscape of the Army Collective Training Service (ACTS). This role is pivotal in shaping and governing the enterprise data architecture to ensure it aligns with the ACTS vision and supports data as a mission-critical asset. Working closely with the Data Lead, Enterprise Architect and Chief Engineer, you will design, evolve, and maintain a secure, scalable, and interoperable data architecture, leveraging cloud services from AWS, Azure, and OCP where appropriate. This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Essential Skills and Experience: Proven experience designing and implementing scalable, secure, and interoperable data architectures in complex environments with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services including use of services like S3, Lambda, Glue, Data Factory, etc. Experience designing and supporting implementation of large-scale data pipelines, data warehousing and Lakehouse technologies. Strong skills in conceptual, logical, and physical data modelling using tools like ER/Studio, ERwin, or Sparx EA (preferred). Experience reverse engineering models from existing databases. Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Experience with API management and gateway tools and services. Experience of RESTful APIs for ingesting and exposing data. Proven track record with data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex work in a rapidly changing environment. Strong critical thinker with problem solving aptitude. A working knowledge of MoD or Government IT Security environments and requirements at various classifications. Desirable Skills and Experience: Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift). Exposure to infrastructure-as-code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Relevant Data and Architecture certification such as TOGAF, MODAF, AWS/Azure Certified Data Architect or Solutions Architect, DAMA Certified Data Management Professional (CDMP) JBRP1_UKTJ
Key Responsibilities: Design our scalable, secure and cost-effective cloud hybrid data solution aligned with Omnia enterprise architecture and Army training objectives. Design innovative data models and metadata systems to interpret and enhance business needs, promoting data as a strategic asset. Develop transitional data architectures and road maps in alignment with Omnia digital transformation objectives, enabling the evolution of integrated training solutions. Collaborate with cross-functional teams and partners to ensure data architectural integrity and alignment. Translate complex technical concepts for a non-technical audience, fostering understanding and buy-in from stakeholders. Support horizon scanning to identify and assess emerging technologies and determine their potential impact on leveraging data analytics to improve training delivery. Membership and contribution to the Omnia Architecture Board(s) to review, define, refine and uphold data architectural principles, policies, and standards across Omnia Training. Work with engineering teams to support and guide the implementation of a variety of solutions across multiple domains, in an agile environment. Manage and lead prototyping and research activity as required to realise the best solutions. Provide oversight and advice to engineers undertaking the design of data models and support the management of data dictionaries. Ensure the security and compliance of data environments through the implementation of appropriate architecture principles, security controls and governance frameworks. Author, review and contribute to technical documentation. Produce High- and low-level design artifacts for data storage, processing, and retrieval systems. Stay current with data technologies, making recommendations for use based on business value. Drive the adoption of these technologies. Serve as the Subject Matter Expert (SME) for the Omnia Data Lakehouse, providing strategic guidance, technical oversight, and deep expertise in its architecture, implementation, and optimisation. Who we are looking for: The Data Architect will provide strategic and practical leadership across the data architecture landscape of the Army Collective Training Service (ACTS). This role is pivotal in shaping and governing the enterprise data architecture to ensure it aligns with the ACTS vision and supports data as a mission-critical asset. Working closely with the Data Lead, Enterprise Architect and Chief Engineer, you will design, evolve, and maintain a secure, scalable, and interoperable data architecture, leveraging cloud services from AWS, Azure, and OCP where appropriate. This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Essential Skills and Experience: Proven experience designing and implementing scalable, secure, and interoperable data architectures in complex environments with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services including use of services like S3, Lambda, Glue, Data Factory, etc. Experience designing and supporting implementation of large-scale data pipelines, data warehousing and Lakehouse technologies. Strong skills in conceptual, logical, and physical data modelling using tools like ER/Studio, ERwin, or Sparx EA (preferred). Experience reverse engineering models from existing databases. Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Experience with API management and gateway tools and services. Experience of RESTful APIs for ingesting and exposing data. Proven track record with data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex work in a rapidly changing environment. Strong critical thinker with problem solving aptitude. A working knowledge of MoD or Government IT Security environments and requirements at various classifications. Desirable Skills and Experience: Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift). Exposure to infrastructure-as-code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Relevant Data and Architecture certification such as TOGAF, MODAF, AWS/Azure Certified Data Architect or Solutions Architect, DAMA Certified Data Management Professional (CDMP) JBRP1_UKTJ
22/07/2026
Full time
Key Responsibilities: Design our scalable, secure and cost-effective cloud hybrid data solution aligned with Omnia enterprise architecture and Army training objectives. Design innovative data models and metadata systems to interpret and enhance business needs, promoting data as a strategic asset. Develop transitional data architectures and road maps in alignment with Omnia digital transformation objectives, enabling the evolution of integrated training solutions. Collaborate with cross-functional teams and partners to ensure data architectural integrity and alignment. Translate complex technical concepts for a non-technical audience, fostering understanding and buy-in from stakeholders. Support horizon scanning to identify and assess emerging technologies and determine their potential impact on leveraging data analytics to improve training delivery. Membership and contribution to the Omnia Architecture Board(s) to review, define, refine and uphold data architectural principles, policies, and standards across Omnia Training. Work with engineering teams to support and guide the implementation of a variety of solutions across multiple domains, in an agile environment. Manage and lead prototyping and research activity as required to realise the best solutions. Provide oversight and advice to engineers undertaking the design of data models and support the management of data dictionaries. Ensure the security and compliance of data environments through the implementation of appropriate architecture principles, security controls and governance frameworks. Author, review and contribute to technical documentation. Produce High- and low-level design artifacts for data storage, processing, and retrieval systems. Stay current with data technologies, making recommendations for use based on business value. Drive the adoption of these technologies. Serve as the Subject Matter Expert (SME) for the Omnia Data Lakehouse, providing strategic guidance, technical oversight, and deep expertise in its architecture, implementation, and optimisation. Who we are looking for: The Data Architect will provide strategic and practical leadership across the data architecture landscape of the Army Collective Training Service (ACTS). This role is pivotal in shaping and governing the enterprise data architecture to ensure it aligns with the ACTS vision and supports data as a mission-critical asset. Working closely with the Data Lead, Enterprise Architect and Chief Engineer, you will design, evolve, and maintain a secure, scalable, and interoperable data architecture, leveraging cloud services from AWS, Azure, and OCP where appropriate. This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Essential Skills and Experience: Proven experience designing and implementing scalable, secure, and interoperable data architectures in complex environments with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services including use of services like S3, Lambda, Glue, Data Factory, etc. Experience designing and supporting implementation of large-scale data pipelines, data warehousing and Lakehouse technologies. Strong skills in conceptual, logical, and physical data modelling using tools like ER/Studio, ERwin, or Sparx EA (preferred). Experience reverse engineering models from existing databases. Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Experience with API management and gateway tools and services. Experience of RESTful APIs for ingesting and exposing data. Proven track record with data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex work in a rapidly changing environment. Strong critical thinker with problem solving aptitude. A working knowledge of MoD or Government IT Security environments and requirements at various classifications. Desirable Skills and Experience: Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift). Exposure to infrastructure-as-code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Relevant Data and Architecture certification such as TOGAF, MODAF, AWS/Azure Certified Data Architect or Solutions Architect, DAMA Certified Data Management Professional (CDMP) JBRP1_UKTJ
Location: Warminster, Wiltshire, United Kingdom. Role Type: Hybrid. About us At OMNIA Training, we've brought together some of the UK's most innovative defence training organisations under one powerful mission: to transform the British Army's training system and create the best-trained Army in the world. OMNIA are redefining the British Army's collective training. To do that, we are looking for the best and brightest minds from across the UK. We are backed by British innovation and powered by world-class experts, like you. OMNIA is at the heart of the UK's bold Land Industrial Strategy. The role You'll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you'll work for the British Army, championing innovation, and helping shape the future of military collective training. Key Responsibilities Collaborate with engineering, simulation, customer, third party and training teams to ensure seamless data management and integration across military training environments. Ensure the security and compliance of data environments through the implementation of appropriate security controls and governance frameworks. Author, review and contribute to technical documentation. Coordinate with cross-functional engineering teams-including QA, development, operations, and business SMEs. Assist in the design and implementation of scalable, high-performance data platforms and pipelines. Define and enforce data engineering standards, best practices, and governance frameworks including data lifecycle design, implementation and management. Implement the design and optimisation of data storage, processing, and retrieval strategies. Collaborate with cross-functional teams (data scientists, analysts, software engineers) to align data solutions with business needs. Drive adoption of modern data technologies (e.g., cloud-native platforms, streaming, orchestration tools). Contribute to data quality, security, compliance, and lineage practices across the organisation. Provide technical input and guidance to data engineering team members. Evaluate, select, and integrate new tools, frameworks, and platforms for the data ecosystem. Act as a subject matter expert in data strategy, influencing design decisions. Any other duties required to meet the needs of the programme. Who we are looking for We're after individuals who want to serve. You'll have a mission focus, and the enthusiasm and drive to 'get things done'. You'll want to work in collaboration with other defence training organisations, and the British Army. You won't let bureaucracy get in the way of what needs to be done, you'll learn lessons and share these lessons across the team, you'll understand what it means to put the mission first. The OMNIA Data Engineer will provide hands on technical oversight and management across the Army Collective Training Service (ACTS) data solutions. These will be prominently MODCloud hosted utilising Cloud Services from AWS, Azure, OCP where appropriate. Reporting to the Data Architect, you will play a key role in ensuring the effective design, assurance, transformation, and delivery of data across ACTS services and capabilities. This includes supporting the integration and operational use of data from legacy systems through API driven solutions. This role requires a systems thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Given the programme's focus on modelling and simulation, familiarity with relevant standards and technologies is highly desirable. Essential Skills and Experience Hands on experience with cloud platforms (AWS, Azure, GCP, OCI) and cloud native data services. Extensive experience designing and building large scale data pipelines and platforms. Strong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL). Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Deep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services. Strong programming skills in Python, Java, or Scala for data engineering. Hands on experience with data orchestration and workflow management tools (e.g., Airflow, Dagster, Prefect). Proven track record with data governance, quality, lineage, and security practices. Experience with real time/streaming data technologies, data ingestion/ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Strong proficiency in relational and non relational databases (e.g., PostgreSQL, MongoDB, Cassandra). Deep knowledge of data transformation and ETL pipelines and APIs. Desirable Skills and Experience Degree in Data Engineering or equivalent professional accreditation such as CEng. Experience with graph databases and advanced query languages (e.g., Neo4j, Gremlin). Knowledge of machine learning data pipelines and MLOps practices. Familiarity with data virtualisation and data mesh concepts. Hands on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift and Ceph). Exposure to infrastructure as code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Strong background in performance tuning for high throughput, low latency data systems. Microsoft Certified: Azure Data Engineer Associate, AWS Certified Data Engineer, IBM Data Engineering Professional Certificate or similar. RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.
20/07/2026
Full time
Location: Warminster, Wiltshire, United Kingdom. Role Type: Hybrid. About us At OMNIA Training, we've brought together some of the UK's most innovative defence training organisations under one powerful mission: to transform the British Army's training system and create the best-trained Army in the world. OMNIA are redefining the British Army's collective training. To do that, we are looking for the best and brightest minds from across the UK. We are backed by British innovation and powered by world-class experts, like you. OMNIA is at the heart of the UK's bold Land Industrial Strategy. The role You'll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you'll work for the British Army, championing innovation, and helping shape the future of military collective training. Key Responsibilities Collaborate with engineering, simulation, customer, third party and training teams to ensure seamless data management and integration across military training environments. Ensure the security and compliance of data environments through the implementation of appropriate security controls and governance frameworks. Author, review and contribute to technical documentation. Coordinate with cross-functional engineering teams-including QA, development, operations, and business SMEs. Assist in the design and implementation of scalable, high-performance data platforms and pipelines. Define and enforce data engineering standards, best practices, and governance frameworks including data lifecycle design, implementation and management. Implement the design and optimisation of data storage, processing, and retrieval strategies. Collaborate with cross-functional teams (data scientists, analysts, software engineers) to align data solutions with business needs. Drive adoption of modern data technologies (e.g., cloud-native platforms, streaming, orchestration tools). Contribute to data quality, security, compliance, and lineage practices across the organisation. Provide technical input and guidance to data engineering team members. Evaluate, select, and integrate new tools, frameworks, and platforms for the data ecosystem. Act as a subject matter expert in data strategy, influencing design decisions. Any other duties required to meet the needs of the programme. Who we are looking for We're after individuals who want to serve. You'll have a mission focus, and the enthusiasm and drive to 'get things done'. You'll want to work in collaboration with other defence training organisations, and the British Army. You won't let bureaucracy get in the way of what needs to be done, you'll learn lessons and share these lessons across the team, you'll understand what it means to put the mission first. The OMNIA Data Engineer will provide hands on technical oversight and management across the Army Collective Training Service (ACTS) data solutions. These will be prominently MODCloud hosted utilising Cloud Services from AWS, Azure, OCP where appropriate. Reporting to the Data Architect, you will play a key role in ensuring the effective design, assurance, transformation, and delivery of data across ACTS services and capabilities. This includes supporting the integration and operational use of data from legacy systems through API driven solutions. This role requires a systems thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Given the programme's focus on modelling and simulation, familiarity with relevant standards and technologies is highly desirable. Essential Skills and Experience Hands on experience with cloud platforms (AWS, Azure, GCP, OCI) and cloud native data services. Extensive experience designing and building large scale data pipelines and platforms. Strong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL). Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Deep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services. Strong programming skills in Python, Java, or Scala for data engineering. Hands on experience with data orchestration and workflow management tools (e.g., Airflow, Dagster, Prefect). Proven track record with data governance, quality, lineage, and security practices. Experience with real time/streaming data technologies, data ingestion/ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Strong proficiency in relational and non relational databases (e.g., PostgreSQL, MongoDB, Cassandra). Deep knowledge of data transformation and ETL pipelines and APIs. Desirable Skills and Experience Degree in Data Engineering or equivalent professional accreditation such as CEng. Experience with graph databases and advanced query languages (e.g., Neo4j, Gremlin). Knowledge of machine learning data pipelines and MLOps practices. Familiarity with data virtualisation and data mesh concepts. Hands on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift and Ceph). Exposure to infrastructure as code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Strong background in performance tuning for high throughput, low latency data systems. Microsoft Certified: Azure Data Engineer Associate, AWS Certified Data Engineer, IBM Data Engineering Professional Certificate or similar. RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.
Job Role We are looking for a Data Engineer to design, build and operate scalable data pipelines and data platform capabilities within a modern lakehouse architecture. You will work in a collaborative agile engineering team delivering production grade data solutions using Databricks, Spark, Python and SQL in a cloud environment. The role focuses on developing robust data pipelines, ensuring high data quality and enabling analytics and data product delivery for enterprise clients. Key Responsibilities Design and implement ELT/ETL pipelines using PySpark and Databricks Build scalable batch and streaming data pipelines using Spark and Kafka, develop optimised SQL and Python pipelines for data transformation and integration, and integrate external data sources using REST APIs and data ingestion frameworks Optimise Spark jobs and cluster performance for reliability and cost efficiency, implement data quality checks, validation and monitoring Apply CI/CD practices and version control for pipeline deployment Work closely with solution architects, DevOps engineers and business analysts to deliver data products, produce technical documentation, architecture diagrams and operational runbooks Key Requirements 3+ years experience building production data pipelines Hands on experience with Databricks, Spark and PySpark; experience with Delta Lake, Unity Catalog and Databricks Working experience with data pipeline design, testing and deployment; familiarity with test driven development, CI/CD practices and Git based development Strong collaboration and communication skills Working knowledge of Hadoop REST APIs and Kafka experience Nice to Have Cloud experience with AWS, Azure or GCP; certifications in Databricks, AWS or data engineering Infrastructure as Code (Terraform); orchestration with Airflow or AWS Glue; streaming technologies including Structured Streaming; observability tooling for data pipelines Experience working with regulated industries such as banking or financial services Databricks experience is preferred; training will be offered to strong candidates.
19/07/2026
Full time
Job Role We are looking for a Data Engineer to design, build and operate scalable data pipelines and data platform capabilities within a modern lakehouse architecture. You will work in a collaborative agile engineering team delivering production grade data solutions using Databricks, Spark, Python and SQL in a cloud environment. The role focuses on developing robust data pipelines, ensuring high data quality and enabling analytics and data product delivery for enterprise clients. Key Responsibilities Design and implement ELT/ETL pipelines using PySpark and Databricks Build scalable batch and streaming data pipelines using Spark and Kafka, develop optimised SQL and Python pipelines for data transformation and integration, and integrate external data sources using REST APIs and data ingestion frameworks Optimise Spark jobs and cluster performance for reliability and cost efficiency, implement data quality checks, validation and monitoring Apply CI/CD practices and version control for pipeline deployment Work closely with solution architects, DevOps engineers and business analysts to deliver data products, produce technical documentation, architecture diagrams and operational runbooks Key Requirements 3+ years experience building production data pipelines Hands on experience with Databricks, Spark and PySpark; experience with Delta Lake, Unity Catalog and Databricks Working experience with data pipeline design, testing and deployment; familiarity with test driven development, CI/CD practices and Git based development Strong collaboration and communication skills Working knowledge of Hadoop REST APIs and Kafka experience Nice to Have Cloud experience with AWS, Azure or GCP; certifications in Databricks, AWS or data engineering Infrastructure as Code (Terraform); orchestration with Airflow or AWS Glue; streaming technologies including Structured Streaming; observability tooling for data pipelines Experience working with regulated industries such as banking or financial services Databricks experience is preferred; training will be offered to strong candidates.
The Opportunity Join a team building the data foundations that support the firm's AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm. At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform. This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases. Key Responsibilities Pipeline Engineering Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform. Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability. Ensure data pipelines are production-ready, well tested and operationally supportable. Data Modelling and Curation Develop raw, refined and curated datasets that support analytics, reporting and AI use cases. Apply sound data modelling principles to represent business entities, relationships and historical change accurately. Work with consumers to shape data products that are usable, well documented and aligned to business needs. Data Quality and Reconciliation Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets. Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise. Contribute to clear standards for testing, monitoring and issue resolution. Delivery and Partnership Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations. Communicate clearly on progress, risks, dependencies and design choices. Take a broader role in technical leadership, task breakdown and support for junior engineers. Skills and Experience Required Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise. Strong hands on programming experience in Python or Java. Good working knowledge of SQL, including troubleshooting, optimisation and data analysis. Ability to learn new tools, internal platforms and delivery workflows quickly. Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices. Data Engineering Capability Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering practices within a team. Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers. Understanding of temporal data modelling, including the handling of historical state and change over time. Knowledge of schema design, schema evolution and data compatibility considerations. Understanding of partitioning, clustering and other techniques used to improve data performance at scale. Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys. Practical approach to data quality, reconciliation and root cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Data formats: JSON, Avro, Parquet Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes based deployment approaches where relevant You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important. What We Are Looking For We are looking for engineers who can deliver well structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast paced environment where data platforms support important business outcomes. Strong candidates will typically demonstrate: sound judgement in technical trade offs attention to detail in data correctness and testing a clear and structured approach to problem solving willingness to work closely with stakeholders and partner teams an interest in developing long term expertise within the firm Equal Opportunity Employer Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law. We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:
19/07/2026
Full time
The Opportunity Join a team building the data foundations that support the firm's AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm. At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform. This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases. Key Responsibilities Pipeline Engineering Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform. Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability. Ensure data pipelines are production-ready, well tested and operationally supportable. Data Modelling and Curation Develop raw, refined and curated datasets that support analytics, reporting and AI use cases. Apply sound data modelling principles to represent business entities, relationships and historical change accurately. Work with consumers to shape data products that are usable, well documented and aligned to business needs. Data Quality and Reconciliation Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets. Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise. Contribute to clear standards for testing, monitoring and issue resolution. Delivery and Partnership Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations. Communicate clearly on progress, risks, dependencies and design choices. Take a broader role in technical leadership, task breakdown and support for junior engineers. Skills and Experience Required Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise. Strong hands on programming experience in Python or Java. Good working knowledge of SQL, including troubleshooting, optimisation and data analysis. Ability to learn new tools, internal platforms and delivery workflows quickly. Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices. Data Engineering Capability Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering practices within a team. Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers. Understanding of temporal data modelling, including the handling of historical state and change over time. Knowledge of schema design, schema evolution and data compatibility considerations. Understanding of partitioning, clustering and other techniques used to improve data performance at scale. Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys. Practical approach to data quality, reconciliation and root cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Data formats: JSON, Avro, Parquet Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes based deployment approaches where relevant You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important. What We Are Looking For We are looking for engineers who can deliver well structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast paced environment where data platforms support important business outcomes. Strong candidates will typically demonstrate: sound judgement in technical trade offs attention to detail in data correctness and testing a clear and structured approach to problem solving willingness to work closely with stakeholders and partner teams an interest in developing long term expertise within the firm Equal Opportunity Employer Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law. We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:
As a Principal GCP Data Engineer, you'll be a true subject matter expert in using the data processing and management capabilities of Google Cloud to develop data-driven solutions for our clients. You will typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example. You could be providing technical support, leading an engineering team or working across multiple teams as a subject matter expert who is critical to the success of a large programme of work. Your team members will look to you as a trusted expert and will expect you to define the end-to-end software development lifecycle in line with modern best practices. As part of your responsibilities, you will be expected to: Develop robust data processing jobs using tools such as Google Cloud Dataflow, Dataproc and BigQuery Design and deliver automated data pipelines that use orchestration tools such as Cloud Composer Design end-to-end solutions and contribute to architecture discussions beyond data processing Own the development process for your team, building strong principles and putting robust methods and patterns in place across architecture, scope, code quality and deployments. Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation. Actively define and evolve PA's data engineering standards and practices, ensuring we maintain a shared, modern and robust approach. Lead and influence technical discussions with client stakeholders to achieve the collective buy in required to be successful Coach and mentor team members, regardless of seniority, and work with them to build their expertise and understanding. Qualifications To be successful in this role, you will need to have: Experience delivering and deploying production ready data processing solutions using BigQuery, Pub/Sub, Dataflow and Dataproc Experience developing end to end solutions using batch and streaming frameworks such as Apache Spark and Apache Beam. Expert understanding of when to use a range of data storage technologies including relational/non relational, document, row based/columnar data stores, data warehousing and data lakes. Expert understanding of data pipeline patterns and approaches such as event driven architectures, ETL/ELT, stream processing and data visualisation. Experience working with business owners to translate business requirements into technical specifications and solution designs that satisfies the data requirements of the business. Experience working with metadata management products such as Cloud Data Catalog and Collibra and Data Governance tools like Dataplex Experience in developing solutions on GCP using cloud native principles and patterns. Experience building data quality alerting and data quarantine solutions to ensure downstream datasets can be trusted. Experience implementing CI/CD pipelines using techniques including as git code control/branching, automated tests and automated deployments. Comfortable working in an Agile team using Scrum or Kanban methodologies. In addition to the above, we would be thrilled if you also had: Experience of working on migrations of enterprise scale data platforms including Hadoop and traditional data warehouses An understanding of machine learning model development lifecycle, feature engineering, training and testing Good understanding or hands on experience of Kafka Experience as a DBA or developer on RDBMS such as PostgreSQL, MySQL, Oracle or SQL Server Experience designing data applications to meet non functional requirements such as performance and availability You are pragmatic and already understand that writing code is only part of what a data engineer does. You can clearly communicate with both clients and peers, describing technical issues and solutions in both written and meeting/workshop contexts. You are able to clearly explain technical concepts to non technical audiences at all levels of an organisation. You are able to influence and persuade senior and specialist client stakeholders, potentially across multiple organisational boundaries without direct authority. You are a confident problem solver and troubleshooter. You are confident and generous in sharing your specialist knowledge, ideas and solutions. You are constantly learning and able to make others better by consciously teaching and unconsciously inspiring. Additional information Benefits package at PA: Private medical insurance Interest free season ticket loan 25 days annual leave with the opportunity to buy 5 additional days Company pension scheme Annual performance based bonus Life and Income protection insurance Tax efficient benefits (cycle to work, give as you earn, childcare benefits) Voluntary benefits (Dental, critical illness, spouse/partner life assurance)
18/07/2026
Full time
As a Principal GCP Data Engineer, you'll be a true subject matter expert in using the data processing and management capabilities of Google Cloud to develop data-driven solutions for our clients. You will typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example. You could be providing technical support, leading an engineering team or working across multiple teams as a subject matter expert who is critical to the success of a large programme of work. Your team members will look to you as a trusted expert and will expect you to define the end-to-end software development lifecycle in line with modern best practices. As part of your responsibilities, you will be expected to: Develop robust data processing jobs using tools such as Google Cloud Dataflow, Dataproc and BigQuery Design and deliver automated data pipelines that use orchestration tools such as Cloud Composer Design end-to-end solutions and contribute to architecture discussions beyond data processing Own the development process for your team, building strong principles and putting robust methods and patterns in place across architecture, scope, code quality and deployments. Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation. Actively define and evolve PA's data engineering standards and practices, ensuring we maintain a shared, modern and robust approach. Lead and influence technical discussions with client stakeholders to achieve the collective buy in required to be successful Coach and mentor team members, regardless of seniority, and work with them to build their expertise and understanding. Qualifications To be successful in this role, you will need to have: Experience delivering and deploying production ready data processing solutions using BigQuery, Pub/Sub, Dataflow and Dataproc Experience developing end to end solutions using batch and streaming frameworks such as Apache Spark and Apache Beam. Expert understanding of when to use a range of data storage technologies including relational/non relational, document, row based/columnar data stores, data warehousing and data lakes. Expert understanding of data pipeline patterns and approaches such as event driven architectures, ETL/ELT, stream processing and data visualisation. Experience working with business owners to translate business requirements into technical specifications and solution designs that satisfies the data requirements of the business. Experience working with metadata management products such as Cloud Data Catalog and Collibra and Data Governance tools like Dataplex Experience in developing solutions on GCP using cloud native principles and patterns. Experience building data quality alerting and data quarantine solutions to ensure downstream datasets can be trusted. Experience implementing CI/CD pipelines using techniques including as git code control/branching, automated tests and automated deployments. Comfortable working in an Agile team using Scrum or Kanban methodologies. In addition to the above, we would be thrilled if you also had: Experience of working on migrations of enterprise scale data platforms including Hadoop and traditional data warehouses An understanding of machine learning model development lifecycle, feature engineering, training and testing Good understanding or hands on experience of Kafka Experience as a DBA or developer on RDBMS such as PostgreSQL, MySQL, Oracle or SQL Server Experience designing data applications to meet non functional requirements such as performance and availability You are pragmatic and already understand that writing code is only part of what a data engineer does. You can clearly communicate with both clients and peers, describing technical issues and solutions in both written and meeting/workshop contexts. You are able to clearly explain technical concepts to non technical audiences at all levels of an organisation. You are able to influence and persuade senior and specialist client stakeholders, potentially across multiple organisational boundaries without direct authority. You are a confident problem solver and troubleshooter. You are confident and generous in sharing your specialist knowledge, ideas and solutions. You are constantly learning and able to make others better by consciously teaching and unconsciously inspiring. Additional information Benefits package at PA: Private medical insurance Interest free season ticket loan 25 days annual leave with the opportunity to buy 5 additional days Company pension scheme Annual performance based bonus Life and Income protection insurance Tax efficient benefits (cycle to work, give as you earn, childcare benefits) Voluntary benefits (Dental, critical illness, spouse/partner life assurance)
Location: Warminster, Wiltshire Position Role Type: Hybrid Job Title: Data Architect Function: Engineering Duration: Permanent Hours: Full Time (37 hours per week) Location(s): Warminster Security Clearance: Must be eligible to obtain or currently hold an SC Clearance The role This is more than a job - it's a mission. You will be part of a high-impact, collaborative environment, where we expect everyone to live the values and standards of the British Army. Every person in our team plays a critical role in delivering OMNIA's vision; designing, delivering, and transforming collective training so the British Army is ready to fight and win. You'll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you'll work for the British Army, championing innovation, and helping shape the future of military collective training. Key Responsibilities Design our scalable, secure and cost-effective cloud hybrid data solution aligned with Omnia enterprise architecture and Army training objectives. Design innovative data models and metadata systems to interpret and enhance business needs, promoting data as a strategic asset. Develop transitional data architectures and road maps in alignment with Omnia digital transformation objectives, enabling the evolution of integrated training solutions. Collaborate with cross-functional teams and partners to ensure data architectural integrity and alignment. Translate complex technical concepts for a non-technical audience, fostering understanding and buy-in from stakeholders. Support horizon scanning to identify and assess emerging technologies and determine their potential impact on leveraging data analytics to improve training delivery. Membership and contribution to the Omnia Architecture Board(s) to review, define, refine and uphold data architectural principles, policies, and standards across Omnia Training. Work with engineering teams to support and guide the implementation of a variety of solutions across multiple domains, in an agile environment. Manage and lead prototyping and research activity as required to realise the best solutions. Provide oversight and advice to engineers undertaking the design of data models and support the management of data dictionaries. Ensure the security and compliance of data environments through the implementation of appropriate architecture principles, security controls and governance frameworks. Author, review and contribute to technical documentation. Produce High- and low-level design artifacts for data storage, processing, and retrieval systems. Stay current with data technologies, making recommendations for use based on business value. Drive the adoption of these technologies. Serve as the Subject Matter Expert (SME) for the Omnia Data Lakehouse, providing strategic guidance, technical oversight, and deep expertise in its architecture, implementation, and optimisation. Who we are looking for You'll have a mission focus, and the enthusiasm and drive to 'get things done'. You'll want to work in collaboration with other defence training organisations, and the British Army. You won't let bureaucracy get in the way of what needs to be done, you'll learn lessons and share these lessons across the team. You'll understand what it means to put the mission first. The Data Architect will provide strategic and practical leadership across the data architecture landscape of the Army Collective Training Service (ACTS). This role is pivotal in shaping and governing the enterprise data architecture to ensure it aligns with the ACTS vision and supports data as a mission-critical asset. Working closely with the Data Lead, Enterprise Architect and Chief Engineer, you will design, evolve, and maintain a secure, scalable, and interoperable data architecture, leveraging cloud services from AWS, Azure, and OCP where appropriate. This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Essential Skills and Experience Proven experience designing and implementing scalable, secure, and interoperable data architectures in complex environments with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services including use of services like S3, Lambda, Glue, Data Factory, etc. Experience designing and supporting implementation of large-scale data pipelines, data warehousing and Lakehouse technologies. Strong skills in conceptual, logical, and physical data modelling using tools like ER/Studio, ERwin, or Sparx EA (preferred). Experience reverse engineering models from existing databases. Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Experience with API management and gateway tools and services. Experience of RESTful APIs for ingesting and exposing data. Proven track record with data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex work in a rapidly changing environment. Strong critical thinker with problem solving aptitude. A working knowledge of MoD or Government IT Security environments and requirements at various classifications. Holder of current SC clearance, or the ability to gain it. Desirable Skills and Experience Hands on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift). Exposure to infrastructure-as-code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Relevant Data and Architecture certification such as TOGAF, MODAF, AWS/Azure Certified Data Architect or Solutions Architect, DAMA Certified Data Management Professional (CDMP). What we offer Competitive salaries. 25 days holiday + statutory public holidays, plus opportunity to buy and sell up to 5 days (37hr). Contributory Pension Scheme (up to 10.5% company contribution). Company bonus scheme (discretionary). 6 times salary "Life Assurance" with pension. Flexible Benefits scheme with extensive salary sacrifice schemes, including Health Cashplan, Dental, and Cycle to Work among others. Enhanced sick pay. Enhanced family friendly policies including enhanced maternity, paternity & shared parental leave. Work Culture 37hr working week, although hours may vary depending on role, job requirement or site-specific arrangements. Remote, hybrid and site based working opportunities, dependant on your needs and the requirements of the role. A grownup flexible working culture that is output, not time spent at desk, focussed. More formal flexible working arrangements can also be requested and assessed subject to the role. Please enquire or highlight any request to our Talent Acquisition team to explore the flexible working possibilities. For this role the successful hire will need to be a permanent UK resident and be eligible to obtain or currently hold an SC Clearance.
14/07/2026
Full time
Location: Warminster, Wiltshire Position Role Type: Hybrid Job Title: Data Architect Function: Engineering Duration: Permanent Hours: Full Time (37 hours per week) Location(s): Warminster Security Clearance: Must be eligible to obtain or currently hold an SC Clearance The role This is more than a job - it's a mission. You will be part of a high-impact, collaborative environment, where we expect everyone to live the values and standards of the British Army. Every person in our team plays a critical role in delivering OMNIA's vision; designing, delivering, and transforming collective training so the British Army is ready to fight and win. You'll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you'll work for the British Army, championing innovation, and helping shape the future of military collective training. Key Responsibilities Design our scalable, secure and cost-effective cloud hybrid data solution aligned with Omnia enterprise architecture and Army training objectives. Design innovative data models and metadata systems to interpret and enhance business needs, promoting data as a strategic asset. Develop transitional data architectures and road maps in alignment with Omnia digital transformation objectives, enabling the evolution of integrated training solutions. Collaborate with cross-functional teams and partners to ensure data architectural integrity and alignment. Translate complex technical concepts for a non-technical audience, fostering understanding and buy-in from stakeholders. Support horizon scanning to identify and assess emerging technologies and determine their potential impact on leveraging data analytics to improve training delivery. Membership and contribution to the Omnia Architecture Board(s) to review, define, refine and uphold data architectural principles, policies, and standards across Omnia Training. Work with engineering teams to support and guide the implementation of a variety of solutions across multiple domains, in an agile environment. Manage and lead prototyping and research activity as required to realise the best solutions. Provide oversight and advice to engineers undertaking the design of data models and support the management of data dictionaries. Ensure the security and compliance of data environments through the implementation of appropriate architecture principles, security controls and governance frameworks. Author, review and contribute to technical documentation. Produce High- and low-level design artifacts for data storage, processing, and retrieval systems. Stay current with data technologies, making recommendations for use based on business value. Drive the adoption of these technologies. Serve as the Subject Matter Expert (SME) for the Omnia Data Lakehouse, providing strategic guidance, technical oversight, and deep expertise in its architecture, implementation, and optimisation. Who we are looking for You'll have a mission focus, and the enthusiasm and drive to 'get things done'. You'll want to work in collaboration with other defence training organisations, and the British Army. You won't let bureaucracy get in the way of what needs to be done, you'll learn lessons and share these lessons across the team. You'll understand what it means to put the mission first. The Data Architect will provide strategic and practical leadership across the data architecture landscape of the Army Collective Training Service (ACTS). This role is pivotal in shaping and governing the enterprise data architecture to ensure it aligns with the ACTS vision and supports data as a mission-critical asset. Working closely with the Data Lead, Enterprise Architect and Chief Engineer, you will design, evolve, and maintain a secure, scalable, and interoperable data architecture, leveraging cloud services from AWS, Azure, and OCP where appropriate. This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Essential Skills and Experience Proven experience designing and implementing scalable, secure, and interoperable data architectures in complex environments with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services including use of services like S3, Lambda, Glue, Data Factory, etc. Experience designing and supporting implementation of large-scale data pipelines, data warehousing and Lakehouse technologies. Strong skills in conceptual, logical, and physical data modelling using tools like ER/Studio, ERwin, or Sparx EA (preferred). Experience reverse engineering models from existing databases. Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Experience with API management and gateway tools and services. Experience of RESTful APIs for ingesting and exposing data. Proven track record with data governance, quality, lineage, and security practices. Experience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Experience in, or knowledge of, DevSecOps Tooling and Processes. Self-starter with the ability to appropriately prioritise and plan complex work in a rapidly changing environment. Strong critical thinker with problem solving aptitude. A working knowledge of MoD or Government IT Security environments and requirements at various classifications. Holder of current SC clearance, or the ability to gain it. Desirable Skills and Experience Hands on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift). Exposure to infrastructure-as-code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Relevant Data and Architecture certification such as TOGAF, MODAF, AWS/Azure Certified Data Architect or Solutions Architect, DAMA Certified Data Management Professional (CDMP). What we offer Competitive salaries. 25 days holiday + statutory public holidays, plus opportunity to buy and sell up to 5 days (37hr). Contributory Pension Scheme (up to 10.5% company contribution). Company bonus scheme (discretionary). 6 times salary "Life Assurance" with pension. Flexible Benefits scheme with extensive salary sacrifice schemes, including Health Cashplan, Dental, and Cycle to Work among others. Enhanced sick pay. Enhanced family friendly policies including enhanced maternity, paternity & shared parental leave. Work Culture 37hr working week, although hours may vary depending on role, job requirement or site-specific arrangements. Remote, hybrid and site based working opportunities, dependant on your needs and the requirements of the role. A grownup flexible working culture that is output, not time spent at desk, focussed. More formal flexible working arrangements can also be requested and assessed subject to the role. Please enquire or highlight any request to our Talent Acquisition team to explore the flexible working possibilities. For this role the successful hire will need to be a permanent UK resident and be eligible to obtain or currently hold an SC Clearance.
As a Data Engineer, you will be critical to the successful delivery of the programme, collaborating within matrix organisation, with multi-disciplinary teams within Engineering. We are looking for individuals who want to serve. You'll have a mission focus, and the enthusiasm and drive to deliver. You must be eligible and willing to obtain SC clearance and will be based at Warminster working in a hybrid style. You'll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you'll work for the British Army, championing innovation, and helping shape the future of military collective training. Key Responsibilities Collaborate with engineering, simulation, customer, third party and training teams to ensure seamless data management and integration across military training environments. Ensuring the security and compliance of data environments through the implementation of appropriate security controls and governance frameworks. Author, review and contribute to technical documentation. Coordinate with cross-functional engineering teams-including QA, development, operations, and business SMEs. Assist in the design and implementation of scalable, high-performance data platforms and pipelines. Define and enforce data engineering standards, best practices, and governance frameworks including data lifecycle design, implementation and management. Implement the design and optimisation of data storage, processing, and retrieval strategies. Collaborate with cross-functional teams (data scientists, analysts, software engineers) to align data solutions with business needs. Drive adoption of modern data technologies (e.g., cloud-native platforms, streaming, orchestration tools). Contribute to data quality, security, compliance, and lineage practices across the organisation. Provide technical input and guidance to data engineering team members. Evaluate, select, and integrate new tools, frameworks, and platforms for the data ecosystem. Act as a subject matter expert in data strategy, influencing design decisions. Any other duties required to meet the needs of the programme. Who we are looking for The OMNIA Data Engineer will provide hands on technical oversight and management across the Army Collective Training Service (ACTS) data solutions. These will be prominently MODCloud hosted utilising Cloud Services from AWS, Azure, OCP where appropriate. Reporting to the Data Architect, you will play a key role in ensuring the effective design, assurance, transformation, and delivery of data across ACTS services and capabilities. This includes supporting the integration and operational use of data from legacy systems through API-driven solutions. This role requires a systems thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Given the programme's focus on modelling and simulation, familiarity with relevant standards and technologies is highly desirable. Essential Skills and Experience Hands on experience with cloud platforms (AWS, Azure, GCP, OCI) and cloud native data services. Extensive experience designing and building large scale data pipelines and platforms. Strong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL). Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Deep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services. Strong programming skills in Python, Java, or Scala for data engineering. Hands on experience with data orchestration and workflow management tools (e.g., Airflow, Dagster, Prefect). Proven track record with data governance, quality, lineage, and security practices. Experience with real time/streaming data technologies, data ingestion/ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Strong proficiency in relational and non relational databases (e.g., PostgreSQL, MongoDB, Cassandra). Deep knowledge of data transformation and ETL pipelines and APIs. Security cleared or ability to obtain (SC or above). Desirable Skills and Experience Degree in Data Engineering or equivalent professional accreditation such as CEng. Experience with graph databases and advanced query languages (e.g., Neo4j, Gremlin). Knowledge of machine learning data pipelines and MLOps practices. Familiarity with data virtualisation and data mesh concepts. Hands on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift and Ceph). Exposure to infrastructure as code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Strong background in performance tuning for high throughput, low latency data systems. Microsoft Certified: Azure Data Engineer Associate, AWS Certified Data Engineer, IBM Data Engineering Professional Certificate or similar.
13/07/2026
Full time
As a Data Engineer, you will be critical to the successful delivery of the programme, collaborating within matrix organisation, with multi-disciplinary teams within Engineering. We are looking for individuals who want to serve. You'll have a mission focus, and the enthusiasm and drive to deliver. You must be eligible and willing to obtain SC clearance and will be based at Warminster working in a hybrid style. You'll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you'll work for the British Army, championing innovation, and helping shape the future of military collective training. Key Responsibilities Collaborate with engineering, simulation, customer, third party and training teams to ensure seamless data management and integration across military training environments. Ensuring the security and compliance of data environments through the implementation of appropriate security controls and governance frameworks. Author, review and contribute to technical documentation. Coordinate with cross-functional engineering teams-including QA, development, operations, and business SMEs. Assist in the design and implementation of scalable, high-performance data platforms and pipelines. Define and enforce data engineering standards, best practices, and governance frameworks including data lifecycle design, implementation and management. Implement the design and optimisation of data storage, processing, and retrieval strategies. Collaborate with cross-functional teams (data scientists, analysts, software engineers) to align data solutions with business needs. Drive adoption of modern data technologies (e.g., cloud-native platforms, streaming, orchestration tools). Contribute to data quality, security, compliance, and lineage practices across the organisation. Provide technical input and guidance to data engineering team members. Evaluate, select, and integrate new tools, frameworks, and platforms for the data ecosystem. Act as a subject matter expert in data strategy, influencing design decisions. Any other duties required to meet the needs of the programme. Who we are looking for The OMNIA Data Engineer will provide hands on technical oversight and management across the Army Collective Training Service (ACTS) data solutions. These will be prominently MODCloud hosted utilising Cloud Services from AWS, Azure, OCP where appropriate. Reporting to the Data Architect, you will play a key role in ensuring the effective design, assurance, transformation, and delivery of data across ACTS services and capabilities. This includes supporting the integration and operational use of data from legacy systems through API-driven solutions. This role requires a systems thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Given the programme's focus on modelling and simulation, familiarity with relevant standards and technologies is highly desirable. Essential Skills and Experience Hands on experience with cloud platforms (AWS, Azure, GCP, OCI) and cloud native data services. Extensive experience designing and building large scale data pipelines and platforms. Strong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL). Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Deep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services. Strong programming skills in Python, Java, or Scala for data engineering. Hands on experience with data orchestration and workflow management tools (e.g., Airflow, Dagster, Prefect). Proven track record with data governance, quality, lineage, and security practices. Experience with real time/streaming data technologies, data ingestion/ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub). Strong proficiency in relational and non relational databases (e.g., PostgreSQL, MongoDB, Cassandra). Deep knowledge of data transformation and ETL pipelines and APIs. Security cleared or ability to obtain (SC or above). Desirable Skills and Experience Degree in Data Engineering or equivalent professional accreditation such as CEng. Experience with graph databases and advanced query languages (e.g., Neo4j, Gremlin). Knowledge of machine learning data pipelines and MLOps practices. Familiarity with data virtualisation and data mesh concepts. Hands on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift and Ceph). Exposure to infrastructure as code tools (Terraform, CloudFormation). Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems. Strong background in performance tuning for high throughput, low latency data systems. Microsoft Certified: Azure Data Engineer Associate, AWS Certified Data Engineer, IBM Data Engineering Professional Certificate or similar.
Engineering - Data Engineer - Vice President - London location_on London, Greater London, England, United Kingdom The Opportunity Join a team building the data foundations that support the firm's AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well governed and high performing data use across the firm. At Goldman Sachs, engineering teams shape scalable systems, solve complex technical problems and turn data into action. In data engineering roles, the emphasis is on designing, building and maintaining large scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform. This is a delivery focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases. Key Responsibilities Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform. Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability. Ensure data pipelines are production ready, well tested and operationally supportable. Data Modelling and Curation Develop raw, refined and curated datasets that support analytics, reporting and AI use cases. Apply sound data modelling principles to represent business entities, relationships and historical change accurately. Work with consumers to shape data products that are usable, well documented and aligned to business needs. Data Quality and Reconciliation Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets. Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise. Contribute to clear standards for testing, monitoring and issue resolution. Delivery and Partnership Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations. Communicate clearly on progress, risks, dependencies and design choices. Take a broader role in technical leadership, task breakdown and support for junior engineers. Skills and Experience Required Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise. Strong hands on programming experience in Python or Java. Good working knowledge of SQL, including troubleshooting, optimisation and data analysis. Ability to learn new tools, internal platforms and delivery workflows quickly. Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices. Data Engineering Capability Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering practices within a team. Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers. Understanding of temporal data modelling, including the handling of historical state and change over time. Knowledge of schema design, schema evolution and data compatibility considerations. Understanding of partitioning, clustering and other techniques used to improve data performance at scale. Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys. Practical approach to data quality, reconciliation and root cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes based deployment approaches where relevant What We Are Looking For We are looking for engineers who can deliver well structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast paced environment where data platforms support important business outcomes. Sound judgement in technical trade offs Attention to detail in data correctness and testing A clear and structured approach to problem solving Willingness to work closely with stakeholders and partner teams An interest in developing long term expertise within the firm Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
12/07/2026
Full time
Engineering - Data Engineer - Vice President - London location_on London, Greater London, England, United Kingdom The Opportunity Join a team building the data foundations that support the firm's AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well governed and high performing data use across the firm. At Goldman Sachs, engineering teams shape scalable systems, solve complex technical problems and turn data into action. In data engineering roles, the emphasis is on designing, building and maintaining large scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform. This is a delivery focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases. Key Responsibilities Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform. Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability. Ensure data pipelines are production ready, well tested and operationally supportable. Data Modelling and Curation Develop raw, refined and curated datasets that support analytics, reporting and AI use cases. Apply sound data modelling principles to represent business entities, relationships and historical change accurately. Work with consumers to shape data products that are usable, well documented and aligned to business needs. Data Quality and Reconciliation Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets. Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise. Contribute to clear standards for testing, monitoring and issue resolution. Delivery and Partnership Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations. Communicate clearly on progress, risks, dependencies and design choices. Take a broader role in technical leadership, task breakdown and support for junior engineers. Skills and Experience Required Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise. Strong hands on programming experience in Python or Java. Good working knowledge of SQL, including troubleshooting, optimisation and data analysis. Ability to learn new tools, internal platforms and delivery workflows quickly. Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices. Data Engineering Capability Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering practices within a team. Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers. Understanding of temporal data modelling, including the handling of historical state and change over time. Knowledge of schema design, schema evolution and data compatibility considerations. Understanding of partitioning, clustering and other techniques used to improve data performance at scale. Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys. Practical approach to data quality, reconciliation and root cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes based deployment approaches where relevant What We Are Looking For We are looking for engineers who can deliver well structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast paced environment where data platforms support important business outcomes. Sound judgement in technical trade offs Attention to detail in data correctness and testing A clear and structured approach to problem solving Willingness to work closely with stakeholders and partner teams An interest in developing long term expertise within the firm Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Job Description The Opportunity Join a team building the data foundations that support the firm's AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm. At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform. This is a delivery focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases. Key Responsibilities Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform. Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability. Ensure data pipelines are production ready, well tested and operationally supportable. Data Modelling and Curation Develop raw, refined and curated datasets that support analytics, reporting and AI use cases. Apply sound data modelling principles to represent business entities, relationships and historical change accurately. Work with consumers to shape data products that are usable, well documented and aligned to business needs. Data Quality and Reconciliation Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets. Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise. Contribute to clear standards for testing, monitoring and issue resolution. Delivery and Partnership Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations. Communicate clearly on progress, risks, dependencies and design choices. Take a broader role in technical leadership, task breakdown and support for junior engineers. Skills and Experience Required Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise. Strong hands on programming experience in Python or Java. Good working knowledge of SQL, including troubleshooting, optimisation and data analysis. Ability to learn new tools, internal platforms and delivery workflows quickly. Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices. Data Engineering Capability Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering practices within a team. Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers. Understanding of temporal data modelling, including the handling of historical state and change over time. Knowledge of schema design, schema evolution and data compatibility considerations. Understanding of partitioning, clustering and other techniques used to improve data performance at scale. Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys. Practical approach to data quality, reconciliation and root cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes based deployment approaches where relevant You'll also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important. What We Are Looking For We are looking for engineers who can deliver well structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast paced environment where data platforms support important business outcomes. Stronger candidates will typically demonstrate: Sound judgement in technical trade offs Attention to detail in data correctness and testing A clear and structured approach to problem solving Willingness to work closely with stakeholders and partner teams An interest in developing long term expertise within the firm Job Info Job Identification 169296 Job Category Vice President Posting Date 04/16/2026, 03:14 PM Locations London, Greater London, England, United Kingdom Benefits at Goldman Sachs Read more about the full suite of class leading benefits our firm has to offer. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
12/07/2026
Full time
Job Description The Opportunity Join a team building the data foundations that support the firm's AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm. At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform. This is a delivery focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision making and emerging AI use cases. Role Summary As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases. Key Responsibilities Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform. Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability. Ensure data pipelines are production ready, well tested and operationally supportable. Data Modelling and Curation Develop raw, refined and curated datasets that support analytics, reporting and AI use cases. Apply sound data modelling principles to represent business entities, relationships and historical change accurately. Work with consumers to shape data products that are usable, well documented and aligned to business needs. Data Quality and Reconciliation Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets. Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise. Contribute to clear standards for testing, monitoring and issue resolution. Delivery and Partnership Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations. Communicate clearly on progress, risks, dependencies and design choices. Take a broader role in technical leadership, task breakdown and support for junior engineers. Skills and Experience Required Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise. Strong hands on programming experience in Python or Java. Good working knowledge of SQL, including troubleshooting, optimisation and data analysis. Ability to learn new tools, internal platforms and delivery workflows quickly. Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices. Data Engineering Capability Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering practices within a team. Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers. Understanding of temporal data modelling, including the handling of historical state and change over time. Knowledge of schema design, schema evolution and data compatibility considerations. Understanding of partitioning, clustering and other techniques used to improve data performance at scale. Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys. Practical approach to data quality, reconciliation and root cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes based deployment approaches where relevant You'll also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important. What We Are Looking For We are looking for engineers who can deliver well structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast paced environment where data platforms support important business outcomes. Stronger candidates will typically demonstrate: Sound judgement in technical trade offs Attention to detail in data correctness and testing A clear and structured approach to problem solving Willingness to work closely with stakeholders and partner teams An interest in developing long term expertise within the firm Job Info Job Identification 169296 Job Category Vice President Posting Date 04/16/2026, 03:14 PM Locations London, Greater London, England, United Kingdom Benefits at Goldman Sachs Read more about the full suite of class leading benefits our firm has to offer. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Position: Customer Success Technical Architect (CSTA) Confluent is searching for a Customer Success Technical Architect (CSTA) to act as a trusted technical advisor and advocate, working with our customers to ensure their success, retention, and expansion. The primary objective of this role is to provide technical guidance-including best practices-for the Confluent product suite, partnering with Customer Solutions and cross functional teams such as Sales, Product Management, and Engineering to accelerate time to value, maximize product consumption, and achieve business objectives. Responsibilities The CSTA role is both deeply technical and commercial in nature. You will leverage a technical background (AppDev, SysAdmin, Distributed Computing) to advise customers on their architectures, including patterns and strategies for operating and maturing their Confluent subscription, while also utilizing relationship management skills and industry experience to guide them toward business goals and value based outcomes. Champion and advocate for the customer within Confluent, coordinating across Sales, Product, Services, Support, and Training to drive technical success. Identify technical objections and develop strategies to address adoption blockers. Support customers through technical lifecycle activities such as architecture planning, cluster and security design, monitoring and automation; review and provide guidance on upgrade or migration plans, platform and application hardening ideas, and high availability design. Guide customers up the data streaming maturity curve with recommendations on advanced topics (data mesh, stream processing, utilization optimization, performance tuning). Develop and present periodic customer reviews, including analysis of technical health and operational performance, to Confluent senior management. Document and transfer knowledge to customers and internal teams, enhancing customer self service and supporting Technical Support Engineers and Professional Services. Leverage knowledge of customer environments to influence the Confluent product roadmap. When necessary, dig in to address customer issues alongside Technical Support Engineers and Core Engineering. Required Education Bachelor's Degree Required Technical and Professional Expertise Demonstrated success in a technical field role for a product/SaaS company with enterprise customers. Passion for working on complex technical problems, with a strong understanding of modern infrastructure and streaming technologies; self starter who thrives in a fast paced environment. Excellent interpersonal and communication skills, with the ability to concisely explain tricky issues and complex solutions to a variety of personas. Demonstrated ability to manage multiple customers simultaneously while paying strict attention to detail and delivering results across initiatives such as driving expansion, customer satisfaction, feature adoption, and retention. Hands on knowledge of one or more key cloud vendors (AWS, GCP, Azure) and a solid understanding of cloud networking and security technologies (VPC, Private Link, Private Service Connect, TLS/SSL, SASL). Experience prototyping and analyzing code in multiple languages (Java, Python, Go, etc.). Experience with JVM tuning and troubleshooting. Experience operating Linux; proficient in configuring, tuning, and troubleshooting both RedHat and Debian based distributions. Ability to learn new technologies quickly, coupled with a strong interest in continuous learning. Flexibility to travel up to 20% of the time. Preferred Technical and Professional Experience Experience with Apache Kafka and Apache Flink. Experience helping customers build distributed systems or streaming solutions that use Kafka alongside technologies such as Spark, Flink, Hadoop, Cassandra, etc. Other Relevant Job Details For additional information about location requirements, please discuss with the recruiter following submission of your application. Some travel may be required based on business demand. Company: (8660) IBM United Kingdom Limited Shift: General (daytime) Is this role a commissionable/sales incentive based position? Equal Opportunity Employer IBM is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by applicable law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
10/07/2026
Full time
Position: Customer Success Technical Architect (CSTA) Confluent is searching for a Customer Success Technical Architect (CSTA) to act as a trusted technical advisor and advocate, working with our customers to ensure their success, retention, and expansion. The primary objective of this role is to provide technical guidance-including best practices-for the Confluent product suite, partnering with Customer Solutions and cross functional teams such as Sales, Product Management, and Engineering to accelerate time to value, maximize product consumption, and achieve business objectives. Responsibilities The CSTA role is both deeply technical and commercial in nature. You will leverage a technical background (AppDev, SysAdmin, Distributed Computing) to advise customers on their architectures, including patterns and strategies for operating and maturing their Confluent subscription, while also utilizing relationship management skills and industry experience to guide them toward business goals and value based outcomes. Champion and advocate for the customer within Confluent, coordinating across Sales, Product, Services, Support, and Training to drive technical success. Identify technical objections and develop strategies to address adoption blockers. Support customers through technical lifecycle activities such as architecture planning, cluster and security design, monitoring and automation; review and provide guidance on upgrade or migration plans, platform and application hardening ideas, and high availability design. Guide customers up the data streaming maturity curve with recommendations on advanced topics (data mesh, stream processing, utilization optimization, performance tuning). Develop and present periodic customer reviews, including analysis of technical health and operational performance, to Confluent senior management. Document and transfer knowledge to customers and internal teams, enhancing customer self service and supporting Technical Support Engineers and Professional Services. Leverage knowledge of customer environments to influence the Confluent product roadmap. When necessary, dig in to address customer issues alongside Technical Support Engineers and Core Engineering. Required Education Bachelor's Degree Required Technical and Professional Expertise Demonstrated success in a technical field role for a product/SaaS company with enterprise customers. Passion for working on complex technical problems, with a strong understanding of modern infrastructure and streaming technologies; self starter who thrives in a fast paced environment. Excellent interpersonal and communication skills, with the ability to concisely explain tricky issues and complex solutions to a variety of personas. Demonstrated ability to manage multiple customers simultaneously while paying strict attention to detail and delivering results across initiatives such as driving expansion, customer satisfaction, feature adoption, and retention. Hands on knowledge of one or more key cloud vendors (AWS, GCP, Azure) and a solid understanding of cloud networking and security technologies (VPC, Private Link, Private Service Connect, TLS/SSL, SASL). Experience prototyping and analyzing code in multiple languages (Java, Python, Go, etc.). Experience with JVM tuning and troubleshooting. Experience operating Linux; proficient in configuring, tuning, and troubleshooting both RedHat and Debian based distributions. Ability to learn new technologies quickly, coupled with a strong interest in continuous learning. Flexibility to travel up to 20% of the time. Preferred Technical and Professional Experience Experience with Apache Kafka and Apache Flink. Experience helping customers build distributed systems or streaming solutions that use Kafka alongside technologies such as Spark, Flink, Hadoop, Cassandra, etc. Other Relevant Job Details For additional information about location requirements, please discuss with the recruiter following submission of your application. Some travel may be required based on business demand. Company: (8660) IBM United Kingdom Limited Shift: General (daytime) Is this role a commissionable/sales incentive based position? Equal Opportunity Employer IBM is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by applicable law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
Job Title: DV Cleared Data Engineer Location: Bath Duration: 12 months Rate: Up to £500 per day Note: Must be willing and eligible to go through the DV clearance process Our client, a reputable organisation supporting high-profile government programmes, is hiring a DV Cleared Data Engineer to join a critical, secure environment. This role involves designing, building, and maintaining robust data pipelines and platforms to enable advanced analytics and intelligence operations. What you'll be doing: Develop, optimise, and support scalable data pipelines (batch and streaming) within secure environments. Manage ETL/ELT processes for diverse datasets, ensuring data quality, lineage, and governance. Collaborate with technical and business teams to translate complex requirements into effective data solutions. Maintain Elasticsearch solutions for indexing, search, and real time data discovery. Ensure data platforms meet security, accreditation, and information assurance standards. Contribute to modern data architecture design across cloud and on premise environments. Support Agile delivery teams, including Scrum and SAFe. What you'll bring: Proven experience as a Data Engineer in secure government, defence, or intelligence settings. Strong Python and SQL development skills. Hands on experience with data integration tools like Airflow, NiFi, Azure Data Factory, or AWS Glue. Expertise in Elasticsearch management, indexing, and query optimisation. Knowledge of data modelling, warehousing, and modern data platform architectures. Familiarity with cloud platforms (AWS, Azure, GCP) in secure environments. Understanding of data security, governance, and information assurance. Experience with DevOps practices, CI/CD, and Infrastructure as Code. Desirable: Experience within UK Defence, Intelligence, or National Security sectors. Knowledge of big data tools such as Kafka, Spark, or Hadoop. Support for machine learning or advanced analytics workloads. Experience working with classified datasets and Elastic Stack (ELK). If you're ready to contribute to vital national security projects, apply now!
09/07/2026
Full time
Job Title: DV Cleared Data Engineer Location: Bath Duration: 12 months Rate: Up to £500 per day Note: Must be willing and eligible to go through the DV clearance process Our client, a reputable organisation supporting high-profile government programmes, is hiring a DV Cleared Data Engineer to join a critical, secure environment. This role involves designing, building, and maintaining robust data pipelines and platforms to enable advanced analytics and intelligence operations. What you'll be doing: Develop, optimise, and support scalable data pipelines (batch and streaming) within secure environments. Manage ETL/ELT processes for diverse datasets, ensuring data quality, lineage, and governance. Collaborate with technical and business teams to translate complex requirements into effective data solutions. Maintain Elasticsearch solutions for indexing, search, and real time data discovery. Ensure data platforms meet security, accreditation, and information assurance standards. Contribute to modern data architecture design across cloud and on premise environments. Support Agile delivery teams, including Scrum and SAFe. What you'll bring: Proven experience as a Data Engineer in secure government, defence, or intelligence settings. Strong Python and SQL development skills. Hands on experience with data integration tools like Airflow, NiFi, Azure Data Factory, or AWS Glue. Expertise in Elasticsearch management, indexing, and query optimisation. Knowledge of data modelling, warehousing, and modern data platform architectures. Familiarity with cloud platforms (AWS, Azure, GCP) in secure environments. Understanding of data security, governance, and information assurance. Experience with DevOps practices, CI/CD, and Infrastructure as Code. Desirable: Experience within UK Defence, Intelligence, or National Security sectors. Knowledge of big data tools such as Kafka, Spark, or Hadoop. Support for machine learning or advanced analytics workloads. Experience working with classified datasets and Elastic Stack (ELK). If you're ready to contribute to vital national security projects, apply now!
Responsibilities Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data related technical issues and support their data infrastructure needs. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Qualifications for Data Engineer Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience building and optimizing 'big data' data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores. Strong project management and organizational skills. Experience supporting and working with cross functional teams in a dynamic environment. We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. Experience with AWS cloud services: EC2, EMR, RDS, Redshift Experience with stream processing systems: Storm, Spark Streaming, etc. Experience with object oriented/object function scripting languages: Python, Java, C++, Scala, etc. Salary: 30000 per annum + benefits
07/07/2026
Full time
Responsibilities Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data related technical issues and support their data infrastructure needs. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Qualifications for Data Engineer Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience building and optimizing 'big data' data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores. Strong project management and organizational skills. Experience supporting and working with cross functional teams in a dynamic environment. We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. Experience with AWS cloud services: EC2, EMR, RDS, Redshift Experience with stream processing systems: Storm, Spark Streaming, etc. Experience with object oriented/object function scripting languages: Python, Java, C++, Scala, etc. Salary: 30000 per annum + benefits
Job Title: DV Cleared Data Engineer Location: Bath Duration: 12 months Rate: Up to 500 per day Must be willing and eligible to go through the DV clearance process Our client, a reputable organisation supporting high-profile government programmes, is hiring a DV Cleared Data Engineer to join a critical, secure environment. This role involves designing, building, and maintaining robust data pipelines and platforms to enable advanced analytics and intelligence operations. What you'll be doing: Develop, optimise, and support scalable data pipelines (batch and streaming) within secure environments. Manage ETL/ELT processes for diverse datasets, ensuring data quality, lineage, and governance. Collaborate with technical and business teams to translate complex requirements into effective data solutions. Maintain Elasticsearch solutions for indexing, search, and real-time data discovery. Ensure data platforms meet security, accreditation, and information assurance standards. Contribute to modern data architecture design across cloud and on-premise environments. Support Agile delivery teams, including Scrum and SAFe. What you'll bring: Proven experience as a Data Engineer in secure government, defence, or intelligence settings. Strong Python and SQL development skills. Hands-on experience with data integration tools like Airflow, NiFi, Azure Data Factory, or AWS Glue. Expertise in Elasticsearch management, indexing, and query optimisation. Knowledge of data modelling, warehousing, and modern data platform architectures. Familiarity with cloud platforms (AWS, Azure, GCP) in secure environments. Understanding of data security, governance, and information assurance. Experience with DevOps practices, CI/CD, and Infrastructure as Code. Desirable: Experience within UK Defence, Intelligence, or National Security sectors. Knowledge of big data tools such as Kafka, Spark, or Hadoop. Support for machine learning or advanced analytics workloads. Experience working with classified datasets and Elastic Stack (ELK). If you're ready to contribute to vital national security projects, apply now! If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.
07/07/2026
Contractor
Job Title: DV Cleared Data Engineer Location: Bath Duration: 12 months Rate: Up to 500 per day Must be willing and eligible to go through the DV clearance process Our client, a reputable organisation supporting high-profile government programmes, is hiring a DV Cleared Data Engineer to join a critical, secure environment. This role involves designing, building, and maintaining robust data pipelines and platforms to enable advanced analytics and intelligence operations. What you'll be doing: Develop, optimise, and support scalable data pipelines (batch and streaming) within secure environments. Manage ETL/ELT processes for diverse datasets, ensuring data quality, lineage, and governance. Collaborate with technical and business teams to translate complex requirements into effective data solutions. Maintain Elasticsearch solutions for indexing, search, and real-time data discovery. Ensure data platforms meet security, accreditation, and information assurance standards. Contribute to modern data architecture design across cloud and on-premise environments. Support Agile delivery teams, including Scrum and SAFe. What you'll bring: Proven experience as a Data Engineer in secure government, defence, or intelligence settings. Strong Python and SQL development skills. Hands-on experience with data integration tools like Airflow, NiFi, Azure Data Factory, or AWS Glue. Expertise in Elasticsearch management, indexing, and query optimisation. Knowledge of data modelling, warehousing, and modern data platform architectures. Familiarity with cloud platforms (AWS, Azure, GCP) in secure environments. Understanding of data security, governance, and information assurance. Experience with DevOps practices, CI/CD, and Infrastructure as Code. Desirable: Experience within UK Defence, Intelligence, or National Security sectors. Knowledge of big data tools such as Kafka, Spark, or Hadoop. Support for machine learning or advanced analytics workloads. Experience working with classified datasets and Elastic Stack (ELK). If you're ready to contribute to vital national security projects, apply now! If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.
