DraftKings is looking for a Senior Data Platform Engineer to enhance our data capabilities. In this role, you will own and operate the Databricks infrastructure, ensuring its performance and reliability. You'll build cloud infrastructure with AWS and Terraform while leading engineering projects from design to implementation. The ideal candidate should have 3+ years of relevant experience, strong skills in Python, and knowledge of ML libraries. Join us and shape the technology driving our gaming experiences.
27/07/2026
Full time
DraftKings is looking for a Senior Data Platform Engineer to enhance our data capabilities. In this role, you will own and operate the Databricks infrastructure, ensuring its performance and reliability. You'll build cloud infrastructure with AWS and Terraform while leading engineering projects from design to implementation. The ideal candidate should have 3+ years of relevant experience, strong skills in Python, and knowledge of ML libraries. Join us and shape the technology driving our gaming experiences.
Req ID: FEQ126R19 Location: London The Opportunity: Shaping The Future of Data & AI With Our Largest Customers Data & AI are the engine driving transformation across our customer base. We are seeking a strategic technical leader to collaborate with our most significant, complex enterprise customers to accelerate that transformation across the UK & Ireland. As a Lead Solutions Architect in the UKI Field Engineering practice, you will be an expert in driving organisational transformation through technology, data and AI. You will work with Databricks UKI leadership to identify and engage a select group of customers at the executive level to advise on and drive Databricks adoption to achieve their business objectives. You will demonstrate our builder culture to the highest standards. At Databricks, we believe in "show, not tell", and you will leverage the latest in Data & AI technologies to inspire customer CTOs, VPs and senior leaders to think bigger and go further in democratising Data & AI across their organisations. You will act as a peer leader for the Databricks UKI technical communities, demonstrating thought leadership, working to establish and maintain best practices and collaborating across our leadership teams to drive collective success and develop the next generation of solutions architecture talent. Why You'll Love This Role How You Will Make an Impact Trusted Advisory: You will build authentic partnerships with stakeholders-from developers to C-suite executives-helping them understand the vision of the Databricks Data Intelligence Platform. Strategic Planning: Partner closely with Account Executives & UKI Leadership to design engagement strategies that address the specific needs of our largest customers. Team Coaching: Act as a mentor for the wider practice, guiding them on how to approach complex customer scenarios and engage at an executive level with credibility. Ecosystem Integration: Solution complex engagements involving the broader cloud ecosystem (AWS, Azure, GCP) and third-party tools to ensure a seamless experience for the customer. Thought Leadership: Elevate your profile by leading executive engagement, creating customer-facing content, and speaking at industry events. What We Are Looking For Enterprise Architecture: Experience influencing technology change at a global-scale enterprise level, with a particular focus on Data & AI strategy and implementation. Commercial Awareness: Deep appreciation of customer and vendor commercial motivations and sales cycles. Market Familiarity: Understanding and experience of key Data & AI technology market players, including the major hyperscalers (AWS, Azure, GCP) and key ISVs. Builder Mentality: A bias towards "showing" rather than "telling", preferring to inspire stakeholders through built examples. Technical Expertise: Deep experience in core data & AI technologies, including languages (Python, SQL), frameworks (Apache Spark) and platforms (Databricks, etc). Collaboration: You can orchestrate diverse teams to achieve a common goal and explain complex tech to non-technical leaders. Travel: This role requires travel to customer sites in the UK and London offices (approx. 20-30%). We support flexible scheduling to help manage this travel alongside your personal life. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
27/07/2026
Full time
Req ID: FEQ126R19 Location: London The Opportunity: Shaping The Future of Data & AI With Our Largest Customers Data & AI are the engine driving transformation across our customer base. We are seeking a strategic technical leader to collaborate with our most significant, complex enterprise customers to accelerate that transformation across the UK & Ireland. As a Lead Solutions Architect in the UKI Field Engineering practice, you will be an expert in driving organisational transformation through technology, data and AI. You will work with Databricks UKI leadership to identify and engage a select group of customers at the executive level to advise on and drive Databricks adoption to achieve their business objectives. You will demonstrate our builder culture to the highest standards. At Databricks, we believe in "show, not tell", and you will leverage the latest in Data & AI technologies to inspire customer CTOs, VPs and senior leaders to think bigger and go further in democratising Data & AI across their organisations. You will act as a peer leader for the Databricks UKI technical communities, demonstrating thought leadership, working to establish and maintain best practices and collaborating across our leadership teams to drive collective success and develop the next generation of solutions architecture talent. Why You'll Love This Role How You Will Make an Impact Trusted Advisory: You will build authentic partnerships with stakeholders-from developers to C-suite executives-helping them understand the vision of the Databricks Data Intelligence Platform. Strategic Planning: Partner closely with Account Executives & UKI Leadership to design engagement strategies that address the specific needs of our largest customers. Team Coaching: Act as a mentor for the wider practice, guiding them on how to approach complex customer scenarios and engage at an executive level with credibility. Ecosystem Integration: Solution complex engagements involving the broader cloud ecosystem (AWS, Azure, GCP) and third-party tools to ensure a seamless experience for the customer. Thought Leadership: Elevate your profile by leading executive engagement, creating customer-facing content, and speaking at industry events. What We Are Looking For Enterprise Architecture: Experience influencing technology change at a global-scale enterprise level, with a particular focus on Data & AI strategy and implementation. Commercial Awareness: Deep appreciation of customer and vendor commercial motivations and sales cycles. Market Familiarity: Understanding and experience of key Data & AI technology market players, including the major hyperscalers (AWS, Azure, GCP) and key ISVs. Builder Mentality: A bias towards "showing" rather than "telling", preferring to inspire stakeholders through built examples. Technical Expertise: Deep experience in core data & AI technologies, including languages (Python, SQL), frameworks (Apache Spark) and platforms (Databricks, etc). Collaboration: You can orchestrate diverse teams to achieve a common goal and explain complex tech to non-technical leaders. Travel: This role requires travel to customer sites in the UK and London offices (approx. 20-30%). We support flexible scheduling to help manage this travel alongside your personal life. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It's transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We're not waiting for the future to arrive. We're shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Senior Data Platform Engineer You'll help build the backbone of DraftKings' machine learning capabilities. You'll design, scale, and operate the Databricks and cloud infrastructure that powers automated, reproducible ML workflows across our business. This role blends platform ownership with deep infrastructure engineering - working shoulder to shoulder with Data Science, ML Engineering, and Infrastructure teams to deliver tools and systems that enable data driven decision making at scale. What you'll do as a Senior Data Platform Engineer Own and operate our Databricks infrastructure to ensure performance, reliability, and cost efficiency. Build and manage cloud infrastructure using AWS and infrastructure as code tools like Terraform. Architect and document scalable systems that support reproducible and automated ML workflows. Collaborate with Data Scientists, Data Engineers, ML Engineers, and Infra partners to align platform features with business needs. Lead complex engineering projects from design through implementation and long term support. Continuously assess and improve platform usability, efficiency, and scalability based on industry best practices. Champion technical excellence through peer reviews, mentorship, and deep documentation. What you'll bring At least 3+ years of experience in ML Platform, Data Platform, Infrastructure, or Data Engineering roles. Proven hands on experience with Databricks in a production environment. Strong knowledge of infrastructure as code, especially with Terraform or Pulumi. Proficiency with AWS and container technologies such as Docker and Kubernetes. Solid Python skills and familiarity with ML libraries and tooling (e.g., MLflow, pandas, scikit learn). A track record of owning and operating complex systems at scale. Strong communication skills with the ability to produce clear, technical documentation. Experience working cross functionally in fast paced, collaborative environments. Company Overview DraftKings Inc. (Nasdaq: DKNG) is a digital sports entertainment and gaming company headquartered in Boston. We are a publicly traded technology company committed to responsibly creating the world's favorite games and betting experiences.
27/07/2026
Full time
At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It's transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We're not waiting for the future to arrive. We're shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Senior Data Platform Engineer You'll help build the backbone of DraftKings' machine learning capabilities. You'll design, scale, and operate the Databricks and cloud infrastructure that powers automated, reproducible ML workflows across our business. This role blends platform ownership with deep infrastructure engineering - working shoulder to shoulder with Data Science, ML Engineering, and Infrastructure teams to deliver tools and systems that enable data driven decision making at scale. What you'll do as a Senior Data Platform Engineer Own and operate our Databricks infrastructure to ensure performance, reliability, and cost efficiency. Build and manage cloud infrastructure using AWS and infrastructure as code tools like Terraform. Architect and document scalable systems that support reproducible and automated ML workflows. Collaborate with Data Scientists, Data Engineers, ML Engineers, and Infra partners to align platform features with business needs. Lead complex engineering projects from design through implementation and long term support. Continuously assess and improve platform usability, efficiency, and scalability based on industry best practices. Champion technical excellence through peer reviews, mentorship, and deep documentation. What you'll bring At least 3+ years of experience in ML Platform, Data Platform, Infrastructure, or Data Engineering roles. Proven hands on experience with Databricks in a production environment. Strong knowledge of infrastructure as code, especially with Terraform or Pulumi. Proficiency with AWS and container technologies such as Docker and Kubernetes. Solid Python skills and familiarity with ML libraries and tooling (e.g., MLflow, pandas, scikit learn). A track record of owning and operating complex systems at scale. Strong communication skills with the ability to produce clear, technical documentation. Experience working cross functionally in fast paced, collaborative environments. Company Overview DraftKings Inc. (Nasdaq: DKNG) is a digital sports entertainment and gaming company headquartered in Boston. We are a publicly traded technology company committed to responsibly creating the world's favorite games and betting experiences.
AI Solution Architect - Senior Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13117 Senior AI Solution Architects are required to support the design, implementation and scaling of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI, cloud and data architecture, with experience designing enterprise AI solutions and translating business requirements into scalable technical architectures. You will play a key role in shaping AI architecture strategy, leading technical teams and supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof of concept through to enterprise deployment and optimisation Evaluating and selecting technologies across open source and commercial platforms Designing and integrating AI solutions into existing enterprise systems and applications Working with AI Engineers, Data Scientists and technical teams to support AI delivery and scaling initiatives Supporting AI governance, security, risk and regulatory considerations throughout the delivery lifecycle Supporting architecture governance, technical review boards and design authorities Building relationships with technical and business stakeholders across large scale transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design principles Experience presenting architectural designs to technical and business stakeholders Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI architecture professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. For more information make an application today! Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
27/07/2026
Full time
AI Solution Architect - Senior Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13117 Senior AI Solution Architects are required to support the design, implementation and scaling of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI, cloud and data architecture, with experience designing enterprise AI solutions and translating business requirements into scalable technical architectures. You will play a key role in shaping AI architecture strategy, leading technical teams and supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof of concept through to enterprise deployment and optimisation Evaluating and selecting technologies across open source and commercial platforms Designing and integrating AI solutions into existing enterprise systems and applications Working with AI Engineers, Data Scientists and technical teams to support AI delivery and scaling initiatives Supporting AI governance, security, risk and regulatory considerations throughout the delivery lifecycle Supporting architecture governance, technical review boards and design authorities Building relationships with technical and business stakeholders across large scale transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design principles Experience presenting architectural designs to technical and business stakeholders Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI architecture professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. For more information make an application today! Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
Senior AI Engineer Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13114 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
27/07/2026
Full time
Senior AI Engineer Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13114 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
JOB DESCRIPTION Out of the successful launch of Chase in 2021, we're a new team, with a new mission. We're creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We're people-first. We value collaboration, curiosity and commitment. As a Software Engineer II at JPMorgan Chase within the International Consumer Bank, you will play a crucial role in this initiative, dedicated to delivering an outstanding banking experience to our customers. You will work in a collaborative environment as part of a diverse, inclusive, and geographically distributed team. We are seeking individuals with a curious mindset and a keen interest in new technology. Our engineers are naturally solution-oriented and possess an interest in the financial sector and focus on addressing our customer needs. We work in teams focused on specific products and projects, providing opportunities to engage in areas such as fraud & financial crime prevention, identity services, money transfers, card payments, lending, customer onboarding, core banking, insurance products, rewards campaigns, and servicing innovations. Job Responsibilities Execute well defined components of cloud native platform services, AI applications, and supporting tooling with minimal guidance. Contribute to reusable platform components, libraries, and templates that other teams across ICB compose into their own AI use cases. Apply established resilient patterns within your services; elevate risks or gaps to senior engineers. Develop secure code to protect our customers and ourselves from malicious actors. Investigate and remediate issues within your scope; elevate appropriately; contribute to preventing recurrence. Support release processes aiming for zero downtime, following team standards. Contribute to observability for the platform components and applications you work on; raise anomalies for squad resolution. Contribute to ensuring the platform components and applications you work on meet the needs of the developers and teams who use them, within your scope. Maintain and continuously improve the platform components and AI applications you ship. Embed controls, compliance, and security into the components and applications you build, so that teams adopting them meet their obligations by default. Provide well structured, timely updates on Jira stories to keep the squad informed of progress and issues. Required Qualifications, Capabilities, And Skills Formal training or certification on software engineering concepts and applied experience. Recent hands on professional experience as a back end software engineer. Experience coding in recent versions of Java and Python programming languages. Experience designing and implementing effective tests (unit, component, integration, end to end, performance, etc.). Excellent written and verbal communication skills in English. Familiarity with advanced AI and ML concepts, such as model serving, feature retrieval, Retrieval Augmented Generation (RAG), and Model Context Protocol (MCP). Strong interest in building generative AI applications and tooling. Experience with cloud technologies and distributed systems, RESTful APIs, and web technologies. Preferred Qualifications, Capabilities, And Skills Background in STEM with exposure to machine learning systems. Experience with MLOps frameworks and platforms like MLflow, Amazon SageMaker, Databricks, BentoML, or Arize is a plus. Experience with AI frameworks like LangChain, LangGraph, or Pydantic AI is a plus. Hands on experience with cloud computing platforms like AWS, Azure, or GCP. Experience working in a highly regulated environment or industry. ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first class business in a first class way approach to serving clients drives everything we do. We strive to build trusted, long term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. ABOUT THE TEAM Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
27/07/2026
Full time
JOB DESCRIPTION Out of the successful launch of Chase in 2021, we're a new team, with a new mission. We're creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We're people-first. We value collaboration, curiosity and commitment. As a Software Engineer II at JPMorgan Chase within the International Consumer Bank, you will play a crucial role in this initiative, dedicated to delivering an outstanding banking experience to our customers. You will work in a collaborative environment as part of a diverse, inclusive, and geographically distributed team. We are seeking individuals with a curious mindset and a keen interest in new technology. Our engineers are naturally solution-oriented and possess an interest in the financial sector and focus on addressing our customer needs. We work in teams focused on specific products and projects, providing opportunities to engage in areas such as fraud & financial crime prevention, identity services, money transfers, card payments, lending, customer onboarding, core banking, insurance products, rewards campaigns, and servicing innovations. Job Responsibilities Execute well defined components of cloud native platform services, AI applications, and supporting tooling with minimal guidance. Contribute to reusable platform components, libraries, and templates that other teams across ICB compose into their own AI use cases. Apply established resilient patterns within your services; elevate risks or gaps to senior engineers. Develop secure code to protect our customers and ourselves from malicious actors. Investigate and remediate issues within your scope; elevate appropriately; contribute to preventing recurrence. Support release processes aiming for zero downtime, following team standards. Contribute to observability for the platform components and applications you work on; raise anomalies for squad resolution. Contribute to ensuring the platform components and applications you work on meet the needs of the developers and teams who use them, within your scope. Maintain and continuously improve the platform components and AI applications you ship. Embed controls, compliance, and security into the components and applications you build, so that teams adopting them meet their obligations by default. Provide well structured, timely updates on Jira stories to keep the squad informed of progress and issues. Required Qualifications, Capabilities, And Skills Formal training or certification on software engineering concepts and applied experience. Recent hands on professional experience as a back end software engineer. Experience coding in recent versions of Java and Python programming languages. Experience designing and implementing effective tests (unit, component, integration, end to end, performance, etc.). Excellent written and verbal communication skills in English. Familiarity with advanced AI and ML concepts, such as model serving, feature retrieval, Retrieval Augmented Generation (RAG), and Model Context Protocol (MCP). Strong interest in building generative AI applications and tooling. Experience with cloud technologies and distributed systems, RESTful APIs, and web technologies. Preferred Qualifications, Capabilities, And Skills Background in STEM with exposure to machine learning systems. Experience with MLOps frameworks and platforms like MLflow, Amazon SageMaker, Databricks, BentoML, or Arize is a plus. Experience with AI frameworks like LangChain, LangGraph, or Pydantic AI is a plus. Hands on experience with cloud computing platforms like AWS, Azure, or GCP. Experience working in a highly regulated environment or industry. ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first class business in a first class way approach to serving clients drives everything we do. We strive to build trusted, long term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. ABOUT THE TEAM Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Senior Data Engineer Who We Are Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, and Poland. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of Data Engineering, Software Engineering and AI. We work with enterprises, scale-ups, and government to turn messy, high-value data into products, platforms, and decisions that actually move the needle. We don't do generic. We build things that matter - We engineer data to life . The Role This is a hands on senior engineering role, not an architecture only seat and not a support function. You'll be responsible for technical direction, platform design and architectural decision making. You'll design and build greenfield data platforms, real-time pipelines, and data products for clients who are serious about using data properly. You'll work in small, high calibre teams and operate close to both the problem and the client. If you enjoy solving hard data problems, shaping modern architectures (data mesh, data products, contracts), and delivering real outcomes - this is your lane. What You'll Be Doing Lead Platform & Architecture Design Own the end-to-end architecture of modern, cloud native data platforms Design scalable data ecosystems using data mesh, data products, and data contracts Make high impact architectural decisions across ingestion, storage, processing, and access layers Ensure platforms are secure, compliant, and production grade by design Build Modern Data Platforms Design and deliver cloud native data platforms using Databricks, Snowflake, AWS, and GCP Apply modern architectural patterns: data mesh, data products, and data contracts Integrate deeply with client systems to enable scalable, consumer oriented data access Develop High-Performance Pipelines Build and optimise batch and real time pipelines Work with streaming and event driven tech such as Kafka, Flink, Kinesis, Pub/Sub Orchestrate workflows using Airflow, Dataflow, Glue Work at Scale Process and transform large datasets using Spark and Flink Design systems that perform in production - not just on paper Own Data Storage & Performance Work across relational, NoSQL, and analytical stores (Postgres, BigQuery, Snowflake, Cassandra, MongoDB) Optimise storage formats and access patterns (Parquet, Delta, ORC, Avro) Cloud, Security & Governance Implement secure, compliant data solutions with security by design Embed governance without killing developer velocity Consult and Influence Work directly with clients to understand problems and shape solutions Translate business needs into pragmatic engineering decisions Act as a trusted technical advisor, not just an order taker Technical Leadership & Quality Set engineering standards, patterns, and best practices across teams Review designs and code, providing clear technical direction and mentorship Raise the bar on data quality, testing, observability, and operational excellence What We're Looking For Core Engineering Strength Strong Python and SQL Deep experience with Spark and modern data platforms (Databricks / Snowflake) Solid grasp of cloud data services (AWS or GCP) Architecture & Design Judgement Demonstrated ownership of large-scale data platform architectures Strong data modelling skills and architectural decision making ability Comfortable balancing trade offs between performance, cost, and complexity Data Platform Experience Built and operated large scale data pipelines in production Strong data modelling capability and architectural judgement Comfortable with multiple storage technologies and formats Engineering Discipline Infrastructure-as-code experience (Terraform, Pulumi) CI/CD pipelines using tools like GitHub Actions, ArgoCD Data testing and quality frameworks (dbt, Great Expectations, Soda) Delivery & Consulting Mindset Experience in consulting or professional services environments Strong consulting instincts - able to challenge assumptions and guide clients toward better outcomes Comfortable mentoring senior engineers and influencing technical culture Why Simple Machines You'll work on interesting, high-impact problems You'll build modern platforms, not maintain legacy mess You'll be surrounded by senior engineers who actually know their craft You'll have autonomy, influence, and room to grow If you're a senior data engineer who wants to build properly, think clearly, and deliver real outcomes - we should talk.
27/07/2026
Full time
Senior Data Engineer Who We Are Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, and Poland. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of Data Engineering, Software Engineering and AI. We work with enterprises, scale-ups, and government to turn messy, high-value data into products, platforms, and decisions that actually move the needle. We don't do generic. We build things that matter - We engineer data to life . The Role This is a hands on senior engineering role, not an architecture only seat and not a support function. You'll be responsible for technical direction, platform design and architectural decision making. You'll design and build greenfield data platforms, real-time pipelines, and data products for clients who are serious about using data properly. You'll work in small, high calibre teams and operate close to both the problem and the client. If you enjoy solving hard data problems, shaping modern architectures (data mesh, data products, contracts), and delivering real outcomes - this is your lane. What You'll Be Doing Lead Platform & Architecture Design Own the end-to-end architecture of modern, cloud native data platforms Design scalable data ecosystems using data mesh, data products, and data contracts Make high impact architectural decisions across ingestion, storage, processing, and access layers Ensure platforms are secure, compliant, and production grade by design Build Modern Data Platforms Design and deliver cloud native data platforms using Databricks, Snowflake, AWS, and GCP Apply modern architectural patterns: data mesh, data products, and data contracts Integrate deeply with client systems to enable scalable, consumer oriented data access Develop High-Performance Pipelines Build and optimise batch and real time pipelines Work with streaming and event driven tech such as Kafka, Flink, Kinesis, Pub/Sub Orchestrate workflows using Airflow, Dataflow, Glue Work at Scale Process and transform large datasets using Spark and Flink Design systems that perform in production - not just on paper Own Data Storage & Performance Work across relational, NoSQL, and analytical stores (Postgres, BigQuery, Snowflake, Cassandra, MongoDB) Optimise storage formats and access patterns (Parquet, Delta, ORC, Avro) Cloud, Security & Governance Implement secure, compliant data solutions with security by design Embed governance without killing developer velocity Consult and Influence Work directly with clients to understand problems and shape solutions Translate business needs into pragmatic engineering decisions Act as a trusted technical advisor, not just an order taker Technical Leadership & Quality Set engineering standards, patterns, and best practices across teams Review designs and code, providing clear technical direction and mentorship Raise the bar on data quality, testing, observability, and operational excellence What We're Looking For Core Engineering Strength Strong Python and SQL Deep experience with Spark and modern data platforms (Databricks / Snowflake) Solid grasp of cloud data services (AWS or GCP) Architecture & Design Judgement Demonstrated ownership of large-scale data platform architectures Strong data modelling skills and architectural decision making ability Comfortable balancing trade offs between performance, cost, and complexity Data Platform Experience Built and operated large scale data pipelines in production Strong data modelling capability and architectural judgement Comfortable with multiple storage technologies and formats Engineering Discipline Infrastructure-as-code experience (Terraform, Pulumi) CI/CD pipelines using tools like GitHub Actions, ArgoCD Data testing and quality frameworks (dbt, Great Expectations, Soda) Delivery & Consulting Mindset Experience in consulting or professional services environments Strong consulting instincts - able to challenge assumptions and guide clients toward better outcomes Comfortable mentoring senior engineers and influencing technical culture Why Simple Machines You'll work on interesting, high-impact problems You'll build modern platforms, not maintain legacy mess You'll be surrounded by senior engineers who actually know their craft You'll have autonomy, influence, and room to grow If you're a senior data engineer who wants to build properly, think clearly, and deliver real outcomes - we should talk.
Internetwork Expert is looking for a Senior Data Engineer who will take charge of designing and implementing scalable data platforms. You'll work closely with clients to craft solutions that drive real business outcomes. Your role encompasses leading architecture design, optimizing data pipelines, and ensuring platforms remain secure and compliant. The ideal candidate will have deep expertise in Python and SQL, a solid understanding of cloud services such as AWS or GCP, and experience with modern data platforms including Databricks and Snowflake. This role offers an opportunity to work on high-impact projects in a collaborative environment.
27/07/2026
Full time
Internetwork Expert is looking for a Senior Data Engineer who will take charge of designing and implementing scalable data platforms. You'll work closely with clients to craft solutions that drive real business outcomes. Your role encompasses leading architecture design, optimizing data pipelines, and ensuring platforms remain secure and compliant. The ideal candidate will have deep expertise in Python and SQL, a solid understanding of cloud services such as AWS or GCP, and experience with modern data platforms including Databricks and Snowflake. This role offers an opportunity to work on high-impact projects in a collaborative environment.
Cacheflow, based in London, is seeking a skilled Data Solutions Architect to engage with complex customers, driving the adoption of the Databricks Data Intelligence Platform. In this role, you will develop customer engagement strategies, influence stakeholders, and act as a trusted advisor for significant data analytics architecture. Requires technical expertise in Data Engineering or AI, excellent customer interaction skills, and the ability to thrive in challenging environments. Pyton and SQL knowledge preferred. Up to 60% travel is expected.
27/07/2026
Full time
Cacheflow, based in London, is seeking a skilled Data Solutions Architect to engage with complex customers, driving the adoption of the Databricks Data Intelligence Platform. In this role, you will develop customer engagement strategies, influence stakeholders, and act as a trusted advisor for significant data analytics architecture. Requires technical expertise in Data Engineering or AI, excellent customer interaction skills, and the ability to thrive in challenging environments. Pyton and SQL knowledge preferred. Up to 60% travel is expected.
Job ID: FEQ427R333 Location: London, United Kingdom Industry: Retail/CPG (UKI Enterprise) Recruiter: Dina Hussain At Databricks, our core values are at the heart of everything we do. A culture of proactiveness and a customer centric mindset guides us in creating a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be a vital part of this mission, utilising your technical expertise to demonstrate how our Lakehouse Platform can help customers address their complex data challenges. You'll work with a collaborative, customer focused team who values innovation and creativity, using your skills to create customised solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world! Reporting to the Manager, Field Engineering. The impact you will have Engage with some of Databricks's largest and most complex customers across the UK & Ireland, defining their technical strategies and supporting them in adopting Databricks to achieve their business objectives. Collaborate with Databricks leadership, account teams and field engineers to define and execute customer engagement strategies. Demonstrate our Builder Culture to the highest standards, putting our principle of "show, not tell" into practice, supported by the full breadth of the latest in AI tooling and processes, to inspire customers and Bricksters on the art of the possible. Coach junior Solutions Architects and teams on use case prioritisation and building technical champions. You will influence stakeholders at all organisational levels through complex engagements with the broader cloud ecosystem and third party applications, ensuring they are excited by the Databricks vision and solution strategy. Be a 'champion' for both customers and colleagues, operating as an expert solution architect and trusted advisor for significant data analytics architecture, design, and adoption of the Databricks Lakehouse platform. Contribute to Databricks' technical community engagement by developing customer facing collateral and leading workshops, seminars, and meet ups. Opportunity to continue your development in one of four tracks - technical specialisation, industry vertical thought leadership, strategic customer vision, and people management. What we look for We are seeking a highly motivated and technically skilled individual to join our UK&I Enterprise Solutions Architecture team, which focuses on engaging with our largest and most complex customers, supporting them in executing strategic business change. This role offers the opportunity to be based in the London Office, with regular collaboration across the UK&I region and close alignment with our London based team. Core Technical Qualifications Hands on experience in technical pre sales or consultancy, with a strong background in Data Science - traditional Machine Learning, Deep Learning, Artificial Intelligence or Generative AI. Demonstrated ability to architect end to end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc. Hands on experience and enthusiasm for building with AI based development tooling such as Genie Code, Claude Code, Cursor etc. Strong proficiency in a core programming language (e.g., Python, SQL) and a willingness to learn (or existing knowledge of) Spark. Proficiency with big data analytics technologies and public cloud platforms (AWS, Azure, or GCP). Hands on expertise in designing and delivering complex proofs of concept (PoCs). Pre Sales & Customer Facing Skills Proven ability to engage with customers in a technical sales capacity: challenging assumptions, guiding discussions to clear outcomes, and communicating both technical and business value propositions. Experience in the full pre sales lifecycle, including use case discovery, solution scoping, and delivering complex solution architecture designs to diverse audiences (from engineers to executives). A customer centric mindset with a passion for building client relationships and internal partnerships with account teams. Seniority & Leadership Demonstrated experience in coaching and mentoring junior team members to help them develop their technical and customer facing skills. Logistics Ability to commute to the London office regularly. Willingness and ability to travel approximately % of the time across UK&I and EMEA for customer visits. Nice to Have Databricks or other relevant Cloud/Data certifications. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please consult your local HR representative. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio economic status, veteran status, and other protected characteristics. Compliance If access to export controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
27/07/2026
Full time
Job ID: FEQ427R333 Location: London, United Kingdom Industry: Retail/CPG (UKI Enterprise) Recruiter: Dina Hussain At Databricks, our core values are at the heart of everything we do. A culture of proactiveness and a customer centric mindset guides us in creating a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be a vital part of this mission, utilising your technical expertise to demonstrate how our Lakehouse Platform can help customers address their complex data challenges. You'll work with a collaborative, customer focused team who values innovation and creativity, using your skills to create customised solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world! Reporting to the Manager, Field Engineering. The impact you will have Engage with some of Databricks's largest and most complex customers across the UK & Ireland, defining their technical strategies and supporting them in adopting Databricks to achieve their business objectives. Collaborate with Databricks leadership, account teams and field engineers to define and execute customer engagement strategies. Demonstrate our Builder Culture to the highest standards, putting our principle of "show, not tell" into practice, supported by the full breadth of the latest in AI tooling and processes, to inspire customers and Bricksters on the art of the possible. Coach junior Solutions Architects and teams on use case prioritisation and building technical champions. You will influence stakeholders at all organisational levels through complex engagements with the broader cloud ecosystem and third party applications, ensuring they are excited by the Databricks vision and solution strategy. Be a 'champion' for both customers and colleagues, operating as an expert solution architect and trusted advisor for significant data analytics architecture, design, and adoption of the Databricks Lakehouse platform. Contribute to Databricks' technical community engagement by developing customer facing collateral and leading workshops, seminars, and meet ups. Opportunity to continue your development in one of four tracks - technical specialisation, industry vertical thought leadership, strategic customer vision, and people management. What we look for We are seeking a highly motivated and technically skilled individual to join our UK&I Enterprise Solutions Architecture team, which focuses on engaging with our largest and most complex customers, supporting them in executing strategic business change. This role offers the opportunity to be based in the London Office, with regular collaboration across the UK&I region and close alignment with our London based team. Core Technical Qualifications Hands on experience in technical pre sales or consultancy, with a strong background in Data Science - traditional Machine Learning, Deep Learning, Artificial Intelligence or Generative AI. Demonstrated ability to architect end to end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc. Hands on experience and enthusiasm for building with AI based development tooling such as Genie Code, Claude Code, Cursor etc. Strong proficiency in a core programming language (e.g., Python, SQL) and a willingness to learn (or existing knowledge of) Spark. Proficiency with big data analytics technologies and public cloud platforms (AWS, Azure, or GCP). Hands on expertise in designing and delivering complex proofs of concept (PoCs). Pre Sales & Customer Facing Skills Proven ability to engage with customers in a technical sales capacity: challenging assumptions, guiding discussions to clear outcomes, and communicating both technical and business value propositions. Experience in the full pre sales lifecycle, including use case discovery, solution scoping, and delivering complex solution architecture designs to diverse audiences (from engineers to executives). A customer centric mindset with a passion for building client relationships and internal partnerships with account teams. Seniority & Leadership Demonstrated experience in coaching and mentoring junior team members to help them develop their technical and customer facing skills. Logistics Ability to commute to the London office regularly. Willingness and ability to travel approximately % of the time across UK&I and EMEA for customer visits. Nice to Have Databricks or other relevant Cloud/Data certifications. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please consult your local HR representative. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio economic status, veteran status, and other protected characteristics. Compliance If access to export controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Job Description Join us and shape the future of risk technology with your expertise in data engineering and software development. You will have the opportunity to push boundaries, innovate, and make a meaningful impact on our business. We value diversity, inclusion, and respect, fostering a collaborative environment where your ideas matter. Experience career growth and mobility while working with market-leading technology products. Be part of a team that thrives on creativity and continuous improvement. As a Lead Software Engineer at JPMorgan Chase within the Data Platform & Strategy team within Corporate Risk Technology, you will design, build, and enhance advanced data engineering solutions. You will play a pivotal role in delivering secure, stable, and scalable technology products that support our business objectives. You will collaborate with agile teams, contribute to technical strategy, and drive innovation across multiple technical areas. Your work will help shape the team culture and the impact of our technology solutions. Job Responsibilities Execute creative software solutions, design, development, and technical troubleshooting to solve complex problems Develop secure, high-quality production code for data-intensive applications and review code written by others Identify opportunities to automate remediation of recurring issues and improve operational stability Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale. Drive communities of practice across Software Engineering to promote new and leading-edge technologies Foster a team culture of diversity, opportunity, inclusion, and respect Required Qualifications, Capabilities, and Skills Proficiency in Engineering & Architecture, AI/ML, with hands on experience designing, implementing, testing, and ensuring operational stability of large scale enterprise data platforms Advanced skills in one or more programming languages such as Java, Python, C/C++, or C# Practical experience delivering system design, application development, testing, and operational stability Working knowledge of relational and NoSQL databases and data lake architectures Experience developing, debugging, and maintaining code with modern programming languages and database querying languages Experience in large scale data processing, microservices, API design, Kafka, Redis, MemCached, Observability tools (Dynatrace, Splunk, Grafana), and Orchestration tools (Airflow, Temporal) Demonstrated experience leading effective use of enterprise authorized AI assist ed software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls. Proficiency in automation, continuous delivery methods, and all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies, CI/CD, application resiliency, and security Practical cloud native experience Preferred Qualifications, Capabilities, and Skills Experience with modern data technologies such as Databricks or Snowflake Hands on experience with Spark/PySpark and other big data processing technologies Demonstrated proficiency in software applications and technical processes within disciplines such as data engineering, cloud, artificial intelligence, machine learning, or mobile Knowledge of the financial services industry and their IT systems Equal Opportunity We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
27/07/2026
Full time
Job Description Join us and shape the future of risk technology with your expertise in data engineering and software development. You will have the opportunity to push boundaries, innovate, and make a meaningful impact on our business. We value diversity, inclusion, and respect, fostering a collaborative environment where your ideas matter. Experience career growth and mobility while working with market-leading technology products. Be part of a team that thrives on creativity and continuous improvement. As a Lead Software Engineer at JPMorgan Chase within the Data Platform & Strategy team within Corporate Risk Technology, you will design, build, and enhance advanced data engineering solutions. You will play a pivotal role in delivering secure, stable, and scalable technology products that support our business objectives. You will collaborate with agile teams, contribute to technical strategy, and drive innovation across multiple technical areas. Your work will help shape the team culture and the impact of our technology solutions. Job Responsibilities Execute creative software solutions, design, development, and technical troubleshooting to solve complex problems Develop secure, high-quality production code for data-intensive applications and review code written by others Identify opportunities to automate remediation of recurring issues and improve operational stability Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale. Drive communities of practice across Software Engineering to promote new and leading-edge technologies Foster a team culture of diversity, opportunity, inclusion, and respect Required Qualifications, Capabilities, and Skills Proficiency in Engineering & Architecture, AI/ML, with hands on experience designing, implementing, testing, and ensuring operational stability of large scale enterprise data platforms Advanced skills in one or more programming languages such as Java, Python, C/C++, or C# Practical experience delivering system design, application development, testing, and operational stability Working knowledge of relational and NoSQL databases and data lake architectures Experience developing, debugging, and maintaining code with modern programming languages and database querying languages Experience in large scale data processing, microservices, API design, Kafka, Redis, MemCached, Observability tools (Dynatrace, Splunk, Grafana), and Orchestration tools (Airflow, Temporal) Demonstrated experience leading effective use of enterprise authorized AI assist ed software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls. Proficiency in automation, continuous delivery methods, and all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies, CI/CD, application resiliency, and security Practical cloud native experience Preferred Qualifications, Capabilities, and Skills Experience with modern data technologies such as Databricks or Snowflake Hands on experience with Spark/PySpark and other big data processing technologies Demonstrated proficiency in software applications and technical processes within disciplines such as data engineering, cloud, artificial intelligence, machine learning, or mobile Knowledge of the financial services industry and their IT systems Equal Opportunity We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
Senior Cloud Platform EngineerApplylocations: Cannon Street, Londontime type: Full timeposted on: Posted 24 Days Agojob requisition id: R\_17210 Job Title Senior Cloud Platform Engineer Job Description About IG GroupIG Group (LSEG: IGG) is a leading global fintech company, established in 1974 and headquartered in London. As an innovative member of the FTSE 100, IG Group provides dynamic online trading platforms and a robust educational ecosystem, empowering ambitious individuals worldwide in their pursuit of financial freedom. With operations spanning eighteen countries across Europe, Africa, Asia-Pacific, the Middle East and North America, IG Group offers clients access to approximately 19,000 financial markets, including shares, forex, indices, commodities and crypto.IG is at a pivotal moment. We are moving with real pace and ambition rethinking how we serve clients, how we operate, and how we use technology to do both better. For people who want to be part of building something, rather than maintaining it, this is an unusually good time to join. Your Team You'll be joining a small, close-knit Data platform engineering team of three to five engineers. We're a team that takes quality seriously, looks out for each other, and gets things done without a lot of ceremony. Everyone brings something different across cloud infrastructure, data platform, and developer tooling and we rely on that range to solve problems well.We work across time zones with colleagues in Bengaluru and Kraków, so clear communication and good async habits matter. You won't be siloed into a narrow lane in a team of this size, everyone gets exposure to the breadth of what we do, and everyone's opinion on how we do it counts. Your role in the Team's Success In a small team, a senior hire has an outsized impact - and this role is no different. Here's what success looks like: You raise the floor. Your experience with GCP and AWS means the team spends less time firefighting and more time building. You bring rigour to how we design and review infrastructure, and your instinct for security and reliability makes the whole platform better. You unblock people. Data engineers, ML engineers, and Data teams depend on the platform to move fast. You're the person who understands what they need, builds the right foundations, and makes sure the platform is something people trust rather than work around. You make the IDP real. An IDP is only useful if it's kept alive and relevant. You'll be one of the people who makes sure it reflects reality - that services are catalogued, templates are current, and engineers across the business can actually find what they're looking for. You help the team get smarter. Whether it's sharing a better way to use AI tooling, writing a clearer runbook, or spotting a pattern we've been missing - you make the people around you better at their jobs. You own your outcomes. This isn't a team with heavy process or close supervision. You'll be trusted to take work end-to-end, flag when something's wrong, and drive improvements without being asked twice. You speak the business's language. The platform only matters if it delivers something the business can use. You'll spend real time with stakeholders across finance, compliance, BI and data science, understanding what they're trying to achieve, framing the trade-offs in language they can act on, and translating that back into platform decisions.The best person in this role won't just be technically strong - they'll care about the team's success as much as their own, and they'll leave the platform in a better state than they found it. What you'll do Responsibilities . Design and architect scalable cloud infrastructure, developing IaC solutions using Terraform and standardisation initiatives Build, optimise, and maintain CI/CD pipelines for infrastructure deployment, supporting DevOps and DevSecOps best practices across the organisation Operate and evolve GCP data platform services - BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub - in close collaboration with data and ML engineering teams Support IAM, service account design, and security posture across the platform, enforcing least-privilege principles Lead incident response and root cause analysis for platform issues, and drive improvements to reduce recurrence Participate in an on-call rota as the platform's operational coverage matures. Contribute to the development and maintenance of our IDP - adding catalog entries, improving scaffolder templates, and keeping TechDocs accurate Work with data engineering and ML engineering teams to onboard their services and pipelines into the catalog, ensuring ownership and metadata are correctly represented Use AI-assisted engineering tools - including Claude Code - as part of your daily workflow for infrastructure authoring, code review, and documentation Share effective AI patterns and prompting approaches with the team, helping build a culture of thoughtful, safe AI-augmented engineering What you'll need for this role You'll need solid experience in: Cloud Infrastructure & Experience: 4+ years in cloud infrastructure engineering with hands-on experience designing and administering complex platforms in GCP including working knowledge of networking (VPC, VPCSC, Direct Connect) and IaaS/PaaS architectural patterns. Exp Designing and operating Google Cloud Platform - BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub - at production scale Infrastructure-as-Code using Terraform, with real hands-on experience of multi-environment configuration management across cloud providers GitLab CI/CD - building and maintaining pipelines, runners, and merge request workflows Cloud IAM and access control design, with a clear understanding of least-privilege and security best practices Working collaboratively with data or ML engineering teams as a platform provider - not just building infrastructure, but making it usable A consultative approach. You're comfortable working with non-technical stakeholders, interpreting requirements, challenging assumptions where needed, and influencing outcomes without retreating into jargon. It would be a bonus if you have: AWS exposure Backstage experience - software catalog configuration, scaffolder templates, or plugin development Familiarity with data platform concepts - medallion architecture, lakehouse patterns, or orchestration tools such as Airflow or dbt Exposure managing Databricks Practical experience with AI coding assistants (Claude Code, GitHub Copilot, Cursor, or similar) in a professional engineering context Experience working in regulated financial services environments The Perks Your growth fuels our success! Thrive with tailored development programs, mentoring opportunities with leaders, and clear career progression. Expand your network through committees, sports and social clubs. Enjoy extra time off for volunteering and community work. Competitive salary Flexible Benefits Package on top of your salary (12%) Private medical cover for you and your family Life insurance Contribution to gym memberships 25 Days holiday, with 1 additional day off to celebrate your Birthday & 2 additional days off a year for voluntary work (28 in total The option to buy or sell holiday days. Unlimited access to the LinkedIn Learning Platform A comprehensive global and local onboarding process Employee-led LGBTQ+, Women's, Black and Parents & Carers networks with an annual budget for organising events & projects that foster an open, diverse and inclusive culture Option to participate and create ESG initiatives based on IG Brighter Future Fund Enhanced primary (maternity), secondary (paternity), and shared parental pay and leave, as well as a range of support and benefits for parents
27/07/2026
Full time
Senior Cloud Platform EngineerApplylocations: Cannon Street, Londontime type: Full timeposted on: Posted 24 Days Agojob requisition id: R\_17210 Job Title Senior Cloud Platform Engineer Job Description About IG GroupIG Group (LSEG: IGG) is a leading global fintech company, established in 1974 and headquartered in London. As an innovative member of the FTSE 100, IG Group provides dynamic online trading platforms and a robust educational ecosystem, empowering ambitious individuals worldwide in their pursuit of financial freedom. With operations spanning eighteen countries across Europe, Africa, Asia-Pacific, the Middle East and North America, IG Group offers clients access to approximately 19,000 financial markets, including shares, forex, indices, commodities and crypto.IG is at a pivotal moment. We are moving with real pace and ambition rethinking how we serve clients, how we operate, and how we use technology to do both better. For people who want to be part of building something, rather than maintaining it, this is an unusually good time to join. Your Team You'll be joining a small, close-knit Data platform engineering team of three to five engineers. We're a team that takes quality seriously, looks out for each other, and gets things done without a lot of ceremony. Everyone brings something different across cloud infrastructure, data platform, and developer tooling and we rely on that range to solve problems well.We work across time zones with colleagues in Bengaluru and Kraków, so clear communication and good async habits matter. You won't be siloed into a narrow lane in a team of this size, everyone gets exposure to the breadth of what we do, and everyone's opinion on how we do it counts. Your role in the Team's Success In a small team, a senior hire has an outsized impact - and this role is no different. Here's what success looks like: You raise the floor. Your experience with GCP and AWS means the team spends less time firefighting and more time building. You bring rigour to how we design and review infrastructure, and your instinct for security and reliability makes the whole platform better. You unblock people. Data engineers, ML engineers, and Data teams depend on the platform to move fast. You're the person who understands what they need, builds the right foundations, and makes sure the platform is something people trust rather than work around. You make the IDP real. An IDP is only useful if it's kept alive and relevant. You'll be one of the people who makes sure it reflects reality - that services are catalogued, templates are current, and engineers across the business can actually find what they're looking for. You help the team get smarter. Whether it's sharing a better way to use AI tooling, writing a clearer runbook, or spotting a pattern we've been missing - you make the people around you better at their jobs. You own your outcomes. This isn't a team with heavy process or close supervision. You'll be trusted to take work end-to-end, flag when something's wrong, and drive improvements without being asked twice. You speak the business's language. The platform only matters if it delivers something the business can use. You'll spend real time with stakeholders across finance, compliance, BI and data science, understanding what they're trying to achieve, framing the trade-offs in language they can act on, and translating that back into platform decisions.The best person in this role won't just be technically strong - they'll care about the team's success as much as their own, and they'll leave the platform in a better state than they found it. What you'll do Responsibilities . Design and architect scalable cloud infrastructure, developing IaC solutions using Terraform and standardisation initiatives Build, optimise, and maintain CI/CD pipelines for infrastructure deployment, supporting DevOps and DevSecOps best practices across the organisation Operate and evolve GCP data platform services - BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub - in close collaboration with data and ML engineering teams Support IAM, service account design, and security posture across the platform, enforcing least-privilege principles Lead incident response and root cause analysis for platform issues, and drive improvements to reduce recurrence Participate in an on-call rota as the platform's operational coverage matures. Contribute to the development and maintenance of our IDP - adding catalog entries, improving scaffolder templates, and keeping TechDocs accurate Work with data engineering and ML engineering teams to onboard their services and pipelines into the catalog, ensuring ownership and metadata are correctly represented Use AI-assisted engineering tools - including Claude Code - as part of your daily workflow for infrastructure authoring, code review, and documentation Share effective AI patterns and prompting approaches with the team, helping build a culture of thoughtful, safe AI-augmented engineering What you'll need for this role You'll need solid experience in: Cloud Infrastructure & Experience: 4+ years in cloud infrastructure engineering with hands-on experience designing and administering complex platforms in GCP including working knowledge of networking (VPC, VPCSC, Direct Connect) and IaaS/PaaS architectural patterns. Exp Designing and operating Google Cloud Platform - BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub - at production scale Infrastructure-as-Code using Terraform, with real hands-on experience of multi-environment configuration management across cloud providers GitLab CI/CD - building and maintaining pipelines, runners, and merge request workflows Cloud IAM and access control design, with a clear understanding of least-privilege and security best practices Working collaboratively with data or ML engineering teams as a platform provider - not just building infrastructure, but making it usable A consultative approach. You're comfortable working with non-technical stakeholders, interpreting requirements, challenging assumptions where needed, and influencing outcomes without retreating into jargon. It would be a bonus if you have: AWS exposure Backstage experience - software catalog configuration, scaffolder templates, or plugin development Familiarity with data platform concepts - medallion architecture, lakehouse patterns, or orchestration tools such as Airflow or dbt Exposure managing Databricks Practical experience with AI coding assistants (Claude Code, GitHub Copilot, Cursor, or similar) in a professional engineering context Experience working in regulated financial services environments The Perks Your growth fuels our success! Thrive with tailored development programs, mentoring opportunities with leaders, and clear career progression. Expand your network through committees, sports and social clubs. Enjoy extra time off for volunteering and community work. Competitive salary Flexible Benefits Package on top of your salary (12%) Private medical cover for you and your family Life insurance Contribution to gym memberships 25 Days holiday, with 1 additional day off to celebrate your Birthday & 2 additional days off a year for voluntary work (28 in total The option to buy or sell holiday days. Unlimited access to the LinkedIn Learning Platform A comprehensive global and local onboarding process Employee-led LGBTQ+, Women's, Black and Parents & Carers networks with an annual budget for organising events & projects that foster an open, diverse and inclusive culture Option to participate and create ESG initiatives based on IG Brighter Future Fund Enhanced primary (maternity), secondary (paternity), and shared parental pay and leave, as well as a range of support and benefits for parents
Tower (tower.dev) is a Python-native serverless data platform company. Data teams write plain Python, and Tower handles packaging, dependency resolution, scheduling, and execution across a serverless runtime built on Apache Iceberg. The product aims to let local Python scripts run in production at scale without a Databricks detour. The team is small and senior, split between London and Berlin. Senior Backend / Platform Engineer (Hybrid) The work is deep systems work including scheduling, distributed execution, and performance. Stack includes Go and Rust for the platform, Python everywhere it matters, Kubernetes (EKS + Karpenter) on AWS, RDS Postgres, ElastiCache Redis, S3 / Iceberg, and WorkOS for auth. Looking for: strong distributed-systems fundamentals comfort owning a system end to end taste for correctness under load Bonus: data-platform, query-engine, or Iceberg experience async Rust Kubernetes internals
27/07/2026
Full time
Tower (tower.dev) is a Python-native serverless data platform company. Data teams write plain Python, and Tower handles packaging, dependency resolution, scheduling, and execution across a serverless runtime built on Apache Iceberg. The product aims to let local Python scripts run in production at scale without a Databricks detour. The team is small and senior, split between London and Berlin. Senior Backend / Platform Engineer (Hybrid) The work is deep systems work including scheduling, distributed execution, and performance. Stack includes Go and Rust for the platform, Python everywhere it matters, Kubernetes (EKS + Karpenter) on AWS, RDS Postgres, ElastiCache Redis, S3 / Iceberg, and WorkOS for auth. Looking for: strong distributed-systems fundamentals comfort owning a system end to end taste for correctness under load Bonus: data-platform, query-engine, or Iceberg experience async Rust Kubernetes internals
Databricks is seeking a Senior Solutions Architect for Enterprise Accounts in London to guide customers through complex data challenges using the Databricks Lakehouse platform. You will partner with Account Executives and engineers to design scalable data solutions across diverse industries. The role emphasizes customer engagement, pre-sales leadership, and hands-on architecture across cloud platforms, with travel to client sites up to 60%.
27/07/2026
Full time
Databricks is seeking a Senior Solutions Architect for Enterprise Accounts in London to guide customers through complex data challenges using the Databricks Lakehouse platform. You will partner with Account Executives and engineers to design scalable data solutions across diverse industries. The role emphasizes customer engagement, pre-sales leadership, and hands-on architecture across cloud platforms, with travel to client sites up to 60%.
Select how often (in days) to receive an alert: Solutions Architect Department: INFORMATION TECHNOLOGY City: London Location: GB INTRODUCTION At Burberry, we believe creativity opens spaces. Our purpose is to unlock the power of imagination to push boundaries and open new possibilities for our people, our customers and our communities. This is the core belief that has guided Burberry since it was founded in 1856 and is central to how we operate as a company today. We aim to provide an environment for creative minds from different backgrounds to thrive, bringing a wide range of skills and experiences to everything we do. As a purposeful, values-driven brand, we are committed to being a force for good in the world as well, creating the next generation of sustainable luxury for customers, driving industry change and championing our communities. JOB PURPOSE The Data Platform Architect is accountable for the technical architecture of the enterprise data platform, ensuring it meets the demands of a growing data estate while maintaining performance, cost efficiency, security, and alignment with enterprise architecture standards. This role will be expected to own the internal technical architecture (compute and storage design, ingestion framework patterns, data modelling standards, andaccess control architecture, platform performance and capacity planning, and establishing architectural authority, documenting design decisions, and ensuring knowledge retention within Burberry. This role defines the architecture, sets the standards, provides design governance, and ensures what is built is consistent, scalable, and aligned to the enterprise technology strategy. The architect participates in cross-functional squads where architectural input is required, providing design guidance for complex data initiatives. ACCOUNTABILITY BOUNDARIES AND KEY INTERFACES Accountable for platform architecture, standards, technical guardrails, architectural roadmap and design assurance for the enterprise data platform. Not accountable for day-to-day platform operations or individual data product delivery, but accountable for the architectural standards those teams consume. Key interfaces include Enterprise Data, Enterprise Platforms & Operations, Data Governance, Cyber Security, Solution Architecture, MLOps/AI teams and strategic technology vendors. RESPONSIBILITIES Design and maintain the platform's technical architecture, including compute/storage design, ingestion frameworks, access control, performance tuning, and capacity planning. Define and maintain architectural standards and guardrails (naming conventions, environment management, deployment pipelines, partitioning strategies, and cost optimisation patterns). Own platform cost modelling and FinOps governance, defining cost allocation patterns and identifying optimisation opportunities. Align with the Data Senior Solution Architect and Data Solution Architects to ensure consistency with enterprise data architecture and models. Translate architectural direction into practical engineering guidance for Data Platform Engineers and Data Engineers, ensuring teams can implement within defined standards without requiring bespoke architectural intervention for standard use cases. Design data ingestion architecture (batch, micro-batch, and streaming) with clear boundaries for system-to-system integration. Define architecture for the semantic layer and self-serve analytics infrastructure. Provide input to data squads for complex data products and support Data Product Managers and Data Engineers where architectural complexity requires it. Ensure architecture supports emerging requirements, including agentic AI data infrastructure, MLOps productionisation, and advanced analytics. Collaborate with the Senior Manager, Data Platform Engineering (within the Enterprise Platforms & Operations team) to ensure platform operations are aligned to the target architecture, providing feedback on feasibility and translating architectural decisions into implementable guidance. Collaborate with the Senior Manager, Data Engineering (within the Enterprise Data team) to ensure data engineering work follows defined patterns and standards. Own the data platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g.,SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions). Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions. Provide architectural input to vendor and tooling decisions, evaluating technology options and providing recommendations for platform evolution. Maintain comprehensive documentation of design decisions, patterns, standards, and trade-offs. Define non-functional platform architecture standards covering resilience, backup/restore, disaster recovery, observability, service levels, auditability and operational readiness. Define platform security and privacy architecture in partnership with Cyber Security and Data Governance, including PII handling, access recertification, audit logging and retention patterns. Establish architecture decision records, exception/waiver processes and design scorecards so deviations from platform standards are visible, time-bound and governed. Maintain platform adoption, performance, cost and standards-compliance metrics, using them to guide roadmap priorities and architecture governance decisions. PERSONAL PROFILE Deep expertise in Databricks (Unity Catalog, Delta Lake, Spark, Databricks SQL) or equivalent Lakehouse platforms, including administration, cost management, and performance optimisation. Strong understanding of cloud-native architecture principles, cost models, and practical experience with CI/CD pipelines and environment strategies. Proven implementation of data security (encryption, RBAC, column/row-level security, data masking). Strong understanding of ingestion and pipeline architecture patterns for diverse source systems. Experience with SAP data landscapes (BW, Datasphere, S/4HANA data flows) is highly desirable given the Burberry technology estate. Experience defining architectural standards and patterns that engineering teams implement and comfortable setting direction without hands-on delivery. Experience working within a centralised architecture function that engages flexibly with delivery squads. Ability to communicate architectural decisions to both technical and non-technical stakeholders. Experience establishing architectural authority in environments transitioning from outsourced to in-house ownership is beneficial. Experience defining non-functional requirements and architecture patterns for enterprise-grade resilience, observability, disaster recovery, data lifecycle management and operational readiness. Experience using architecture decision records, design authorities, exception management and measurable standards adoption to embed architectural governance without slowing delivery.
27/07/2026
Full time
Select how often (in days) to receive an alert: Solutions Architect Department: INFORMATION TECHNOLOGY City: London Location: GB INTRODUCTION At Burberry, we believe creativity opens spaces. Our purpose is to unlock the power of imagination to push boundaries and open new possibilities for our people, our customers and our communities. This is the core belief that has guided Burberry since it was founded in 1856 and is central to how we operate as a company today. We aim to provide an environment for creative minds from different backgrounds to thrive, bringing a wide range of skills and experiences to everything we do. As a purposeful, values-driven brand, we are committed to being a force for good in the world as well, creating the next generation of sustainable luxury for customers, driving industry change and championing our communities. JOB PURPOSE The Data Platform Architect is accountable for the technical architecture of the enterprise data platform, ensuring it meets the demands of a growing data estate while maintaining performance, cost efficiency, security, and alignment with enterprise architecture standards. This role will be expected to own the internal technical architecture (compute and storage design, ingestion framework patterns, data modelling standards, andaccess control architecture, platform performance and capacity planning, and establishing architectural authority, documenting design decisions, and ensuring knowledge retention within Burberry. This role defines the architecture, sets the standards, provides design governance, and ensures what is built is consistent, scalable, and aligned to the enterprise technology strategy. The architect participates in cross-functional squads where architectural input is required, providing design guidance for complex data initiatives. ACCOUNTABILITY BOUNDARIES AND KEY INTERFACES Accountable for platform architecture, standards, technical guardrails, architectural roadmap and design assurance for the enterprise data platform. Not accountable for day-to-day platform operations or individual data product delivery, but accountable for the architectural standards those teams consume. Key interfaces include Enterprise Data, Enterprise Platforms & Operations, Data Governance, Cyber Security, Solution Architecture, MLOps/AI teams and strategic technology vendors. RESPONSIBILITIES Design and maintain the platform's technical architecture, including compute/storage design, ingestion frameworks, access control, performance tuning, and capacity planning. Define and maintain architectural standards and guardrails (naming conventions, environment management, deployment pipelines, partitioning strategies, and cost optimisation patterns). Own platform cost modelling and FinOps governance, defining cost allocation patterns and identifying optimisation opportunities. Align with the Data Senior Solution Architect and Data Solution Architects to ensure consistency with enterprise data architecture and models. Translate architectural direction into practical engineering guidance for Data Platform Engineers and Data Engineers, ensuring teams can implement within defined standards without requiring bespoke architectural intervention for standard use cases. Design data ingestion architecture (batch, micro-batch, and streaming) with clear boundaries for system-to-system integration. Define architecture for the semantic layer and self-serve analytics infrastructure. Provide input to data squads for complex data products and support Data Product Managers and Data Engineers where architectural complexity requires it. Ensure architecture supports emerging requirements, including agentic AI data infrastructure, MLOps productionisation, and advanced analytics. Collaborate with the Senior Manager, Data Platform Engineering (within the Enterprise Platforms & Operations team) to ensure platform operations are aligned to the target architecture, providing feedback on feasibility and translating architectural decisions into implementable guidance. Collaborate with the Senior Manager, Data Engineering (within the Enterprise Data team) to ensure data engineering work follows defined patterns and standards. Own the data platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g.,SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions). Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions. Provide architectural input to vendor and tooling decisions, evaluating technology options and providing recommendations for platform evolution. Maintain comprehensive documentation of design decisions, patterns, standards, and trade-offs. Define non-functional platform architecture standards covering resilience, backup/restore, disaster recovery, observability, service levels, auditability and operational readiness. Define platform security and privacy architecture in partnership with Cyber Security and Data Governance, including PII handling, access recertification, audit logging and retention patterns. Establish architecture decision records, exception/waiver processes and design scorecards so deviations from platform standards are visible, time-bound and governed. Maintain platform adoption, performance, cost and standards-compliance metrics, using them to guide roadmap priorities and architecture governance decisions. PERSONAL PROFILE Deep expertise in Databricks (Unity Catalog, Delta Lake, Spark, Databricks SQL) or equivalent Lakehouse platforms, including administration, cost management, and performance optimisation. Strong understanding of cloud-native architecture principles, cost models, and practical experience with CI/CD pipelines and environment strategies. Proven implementation of data security (encryption, RBAC, column/row-level security, data masking). Strong understanding of ingestion and pipeline architecture patterns for diverse source systems. Experience with SAP data landscapes (BW, Datasphere, S/4HANA data flows) is highly desirable given the Burberry technology estate. Experience defining architectural standards and patterns that engineering teams implement and comfortable setting direction without hands-on delivery. Experience working within a centralised architecture function that engages flexibly with delivery squads. Ability to communicate architectural decisions to both technical and non-technical stakeholders. Experience establishing architectural authority in environments transitioning from outsourced to in-house ownership is beneficial. Experience defining non-functional requirements and architecture patterns for enterprise-grade resilience, observability, disaster recovery, data lifecycle management and operational readiness. Experience using architecture decision records, design authorities, exception management and measurable standards adoption to embed architectural governance without slowing delivery.
Are you a senior Python engineer who wants to work at the intersection of data platforms and applied AI? This is your opportunity to join a small, high-impact team building something new from the ground up - where your decisions shape the architecture, not just the backlog. At JPMorganChase, we invest in engineers who are curious, pragmatic, and ready to grow into emerging technology stacks. As a Senior Lead Software Engineer at JPMorganChase within the Corporate Technology Data and Analytics Services team, you will be a founding contributor to the Context Plane - a greenfield platform that connects the firm's data mesh and knowledge sources to AI agents and large language model tools. You will own components end-to-end, from ingestion pipelines to governed retrieval services, and your engineering instincts will directly influence how the platform evolves. This is a hands-on senior role with real architectural scope, active cross-functional collaboration, and strong support for internal mobility and upskilling. Job responsibilities Design, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector store Build and evolve the serving layer - including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint consumed by downstream agents Extract and promote reusable components into a shared core library, reducing duplication across the platform's repositories Integrate with data sources and services across the firm, including enterprise AI and large language model gateways Own quality across your components: automated testing, code reviews, observability, and resilient, secure service design Partner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into working, measurable capabilities Contribute to design discussions and agile ceremonies, and actively mentor teammates to raise the engineering bar across the team Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience Demonstrated expertise building production-grade backend services and data pipelines in Python Strong command of API design principles (e.g., FastAPI), automated testing, CI/CD practices, and source control workflows Experience designing and building data ingestion or integration pipelines at scale, with attention to data quality and resilience Proficiency working with cloud infrastructure (AWS) and containerized services (Docker/ECS) Ability to own technical components end-to-end - from design through deployment and observability Strong collaboration skills with the ability to work across engineering, product, and data science disciplines Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices Preferred qualifications, capabilities, and skills Experience with graph databases and Cypher query language (e.g., Neo4j) or a strong interest in graph data modeling Familiarity with vector search, embeddings, or retrieval-augmented generation (RAG) patterns Exposure to large language model serving, agentic patterns (tool/function calling, Model Context Protocol), or platforms such as Bedrock or Azure OpenAI Experience with Databricks, MongoDB, or large-scale extract, transform, and load / data integration workflows Knowledge of data governance, lineage, and entitlements concepts in an enterprise environment
27/07/2026
Full time
Are you a senior Python engineer who wants to work at the intersection of data platforms and applied AI? This is your opportunity to join a small, high-impact team building something new from the ground up - where your decisions shape the architecture, not just the backlog. At JPMorganChase, we invest in engineers who are curious, pragmatic, and ready to grow into emerging technology stacks. As a Senior Lead Software Engineer at JPMorganChase within the Corporate Technology Data and Analytics Services team, you will be a founding contributor to the Context Plane - a greenfield platform that connects the firm's data mesh and knowledge sources to AI agents and large language model tools. You will own components end-to-end, from ingestion pipelines to governed retrieval services, and your engineering instincts will directly influence how the platform evolves. This is a hands-on senior role with real architectural scope, active cross-functional collaboration, and strong support for internal mobility and upskilling. Job responsibilities Design, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector store Build and evolve the serving layer - including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint consumed by downstream agents Extract and promote reusable components into a shared core library, reducing duplication across the platform's repositories Integrate with data sources and services across the firm, including enterprise AI and large language model gateways Own quality across your components: automated testing, code reviews, observability, and resilient, secure service design Partner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into working, measurable capabilities Contribute to design discussions and agile ceremonies, and actively mentor teammates to raise the engineering bar across the team Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience Demonstrated expertise building production-grade backend services and data pipelines in Python Strong command of API design principles (e.g., FastAPI), automated testing, CI/CD practices, and source control workflows Experience designing and building data ingestion or integration pipelines at scale, with attention to data quality and resilience Proficiency working with cloud infrastructure (AWS) and containerized services (Docker/ECS) Ability to own technical components end-to-end - from design through deployment and observability Strong collaboration skills with the ability to work across engineering, product, and data science disciplines Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices Preferred qualifications, capabilities, and skills Experience with graph databases and Cypher query language (e.g., Neo4j) or a strong interest in graph data modeling Familiarity with vector search, embeddings, or retrieval-augmented generation (RAG) patterns Exposure to large language model serving, agentic patterns (tool/function calling, Model Context Protocol), or platforms such as Bedrock or Azure OpenAI Experience with Databricks, MongoDB, or large-scale extract, transform, and load / data integration workflows Knowledge of data governance, lineage, and entitlements concepts in an enterprise environment
Mission As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers in architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will have Architecting Workloads: Design and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool-calling, multi-agent orchestration, and guardrails), AI observability, and natural language querying of structured data. Provide advanced technical support to Solution Architects during the technical sales cycle by building MVPs, leading deep-dive sessions, and aligning AI solutions with complex customer business challenges. Product Influence: Collaborate cross-functionally with product and engineering teams to represent the voice of the customer, define priorities, and influence the platform's AI roadmap. Thought Leadership: Drive community growth and AI platform adoption through the creation of technical tutorials and training materials, as well as by presenting at industry conferences and leading hackathons. What we look for Experience: 10+ years of hands-on industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning, and deployment tools (e.g., HuggingFace, Langchain). Hands-on experience working with Distributed Spark based systems Experience with data engineering concepts or a good understanding of data engineering concepts Pre-sales or post-sales experience working with external clients across a variety of industry markets. Minimum of 5+ years of customer-facing experience would be preferred Preferred Experience working with Apache Spark to process large-scale distributed datasets Communication: Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences. Core Traits: Passion for lifelong learning, collaboration, and driving business value through AI. Can meet expectations for technical training and role-specific outcomes within 3 months of hire Can travel up to 30% when needed About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region. Our Commitment to Diversity and Inclusion
27/07/2026
Full time
Mission As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers in architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will have Architecting Workloads: Design and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool-calling, multi-agent orchestration, and guardrails), AI observability, and natural language querying of structured data. Provide advanced technical support to Solution Architects during the technical sales cycle by building MVPs, leading deep-dive sessions, and aligning AI solutions with complex customer business challenges. Product Influence: Collaborate cross-functionally with product and engineering teams to represent the voice of the customer, define priorities, and influence the platform's AI roadmap. Thought Leadership: Drive community growth and AI platform adoption through the creation of technical tutorials and training materials, as well as by presenting at industry conferences and leading hackathons. What we look for Experience: 10+ years of hands-on industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning, and deployment tools (e.g., HuggingFace, Langchain). Hands-on experience working with Distributed Spark based systems Experience with data engineering concepts or a good understanding of data engineering concepts Pre-sales or post-sales experience working with external clients across a variety of industry markets. Minimum of 5+ years of customer-facing experience would be preferred Preferred Experience working with Apache Spark to process large-scale distributed datasets Communication: Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences. Core Traits: Passion for lifelong learning, collaboration, and driving business value through AI. Can meet expectations for technical training and role-specific outcomes within 3 months of hire Can travel up to 30% when needed About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region. Our Commitment to Diversity and Inclusion
Databricks Inc. is seeking a Senior Specialist Solutions Architect (ML & AI) to act as a trusted technical ML/AI expert for customers and Field Engineering. You will guide enterprise customers in architecting production-grade ML/AI apps on the Databricks Data Intelligence Platform and mentor colleagues. You will work with solution architects, lead GenAI initiatives, and influence the AI roadmap while maintaining cutting-edge expertise in areas like GenAI, MLOps, and LLMOps.
27/07/2026
Full time
Databricks Inc. is seeking a Senior Specialist Solutions Architect (ML & AI) to act as a trusted technical ML/AI expert for customers and Field Engineering. You will guide enterprise customers in architecting production-grade ML/AI apps on the Databricks Data Intelligence Platform and mentor colleagues. You will work with solution architects, lead GenAI initiatives, and influence the AI roadmap while maintaining cutting-edge expertise in areas like GenAI, MLOps, and LLMOps.
Databricks Inc. is hiring a Senior Specialist Solutions Engineer (AI/ML) in London, United Kingdom, for a hybrid position. The role involves guiding customers in architecting ML applications on the Databricks platform, while mentoring and expanding technical skills in GenAI, LLMOps, and ML. Ideal candidates will have technical expertise in ML Engineering, hands-on experience in cloud infrastructure, and a commitment to customer success. Benefits offered include comprehensive perks tailored to regional needs.
27/07/2026
Full time
Databricks Inc. is hiring a Senior Specialist Solutions Engineer (AI/ML) in London, United Kingdom, for a hybrid position. The role involves guiding customers in architecting ML applications on the Databricks platform, while mentoring and expanding technical skills in GenAI, LLMOps, and ML. Ideal candidates will have technical expertise in ML Engineering, hands-on experience in cloud infrastructure, and a commitment to customer success. Benefits offered include comprehensive perks tailored to regional needs.
Principal Data Architect DV Cleared Secure Government & Defence Programmes UK Hybrid + client site Active DV clearance non-negotiable Architecture that ends up in service, not in a slide pack. Datatech Analytics is supporting a leading UK consulting and technology organisation building secure, enterprise-scale data platforms across defence, national security and classified government programmes. We're engaging Principal Data Architects who want ownership, not oversight. The role You'll set and lead the technical direction of large-scale data platforms on mission-critical programmes working alongside senior stakeholders, engineers and delivery teams. Not advisory. You stay close to delivery and shape how platforms get built, deployed and used. What you'll do - Own enterprise data architecture across secure programmes - Design end-to-end platforms ingestion through to analytics and operational use - Build secure, scalable architectures for highly classified environments - Turn complex mission requirements into things that ship - Lead engineering teams through implementation - Shape long-term architectural strategy and capability The environment AWS, Azure, GCP Databricks, Snowflake lake, lakehouse and modern warehouse patterns distributed processing DevOps, IaC, secure deployment governance, access control, analytics enablement What we need - Active DV clearance - Track record delivering enterprise-scale data platforms - Defence, national security or secure government background - Deep cloud data architecture and secure design expertise - Credible with senior stakeholders - Led teams through complex delivery Why it matters These programmes sit at the core of the UK's secure data capability. Real constraints, real consequences, no sandbox platforms that support operational decisions when it counts. Confidential conversation: (url removed)
27/07/2026
Full time
Principal Data Architect DV Cleared Secure Government & Defence Programmes UK Hybrid + client site Active DV clearance non-negotiable Architecture that ends up in service, not in a slide pack. Datatech Analytics is supporting a leading UK consulting and technology organisation building secure, enterprise-scale data platforms across defence, national security and classified government programmes. We're engaging Principal Data Architects who want ownership, not oversight. The role You'll set and lead the technical direction of large-scale data platforms on mission-critical programmes working alongside senior stakeholders, engineers and delivery teams. Not advisory. You stay close to delivery and shape how platforms get built, deployed and used. What you'll do - Own enterprise data architecture across secure programmes - Design end-to-end platforms ingestion through to analytics and operational use - Build secure, scalable architectures for highly classified environments - Turn complex mission requirements into things that ship - Lead engineering teams through implementation - Shape long-term architectural strategy and capability The environment AWS, Azure, GCP Databricks, Snowflake lake, lakehouse and modern warehouse patterns distributed processing DevOps, IaC, secure deployment governance, access control, analytics enablement What we need - Active DV clearance - Track record delivering enterprise-scale data platforms - Defence, national security or secure government background - Deep cloud data architecture and secure design expertise - Credible with senior stakeholders - Led teams through complex delivery Why it matters These programmes sit at the core of the UK's secure data capability. Real constraints, real consequences, no sandbox platforms that support operational decisions when it counts. Confidential conversation: (url removed)
