40 jobs found

SoSafe has the ambition to become the leading human risk management provider in Europe. Our award-winning awareness platform triggers behavioural change by providing effective and engaging training and simulations on cybersecurity and data protection. Cybercrime is costing the world >$10 trillion annually and growing by 15% p.a. - we invite you to be part of the solution! Location UK, Ireland, or Portugal (remote). Candidates must have work authorization in one of these countries. Office access available in London, Dublin, and Lisbon. Here's how you'll make a difference: Own the transformation layer in dbt - design, build, and maintain modular, well-tested data models that define how data is structured and consumed across the company. Define and implement core business metrics (e.g. activation, engagement, retention) as reusable, versioned data assets - ensuring consistent definitions across analytics, product, and AI use cases. Model complex SaaS data by integrating product events, CRM (Salesforce), and support data into clean, well-defined fact and dimension models. Build and evolve our semantic layer - creating a reliable abstraction over our data that enables consistent KPI definitions and supports downstream consumers, including LLM-based analytics agents. Collaborate with Data Engineers on upstream data contracts and event schemas - ensuring raw data is structured in a way that supports scalable, reliable analytics. Establish and enforce best practices in testing, documentation, and data quality - making these part of the standard development lifecycle. Document models, metrics, and lineage clearly - enabling self-service and reducing ambiguity across teams. What you bring 5+ years in analytics engineering or data engineering with a strong focus on data modeling Strong proficiency in dbt and SQL - building modular, well-tested models Solid understanding of dimensional modeling and metric design Experience working with cloud data warehouses (BigQuery, Snowflake, or Redshift) Experience with metrics / semantic layers (e.g. dbt metrics, MetricFlow, Cube) Strong data quality mindset (testing, validation, monitoring) Comfortable working with event-based data and cross-functional teams Able to turn ambiguous business questions into clear data models Strong business acumen with the ability to challenge metric definitions and ensure they reflect real business outcomes Fluent in English. Nice to have Familiarity with how LLMs consume structured data - e.g. semantic layers, metrics registries, YAML-based context - and an interest in building data infrastructure that serves AI agents, not just BI tools. Experience modeling product usage data (event-based or session-based). What we offer Work/Life balance: Flexible hours, 33 vacation days Wellbeing and financial support: Access to Open Up, corporate discounts Connection & community: Virtual events, collaborative team activities, and opportunities for local meet-ups And the list goes on: Tech equipment, referral bonuses, dog-friendly HQ Perks and benefits listed above are for full-time employees and may vary slightly by office location. These are just a sample - you'll learn more during the interview process. About Us At SoSafe, we're on a mission to make the digital world safer by addressing the human factor in cybersecurity. As one of the fastest-growing security awareness scale-ups worldwide, we leverage behavioural science and data-driven learning to empower people against cyber threats. Our Human Risk Management approach helps organisations turn their employees into their strongest line of defence. Backed by leading VCs like Highland Europe and Global Founders Capital, we're rapidly expanding across the globe. We're looking for team players who want to drive meaningful change in cybersecurity, take ownership of their work, and grow with us. If you thrive in a vibrant, purpose-driven environment that values innovation, diversity, and collaboration, then this is the place for you!

Data Architect Department: Data Employment Type: Contract Location: London Reporting To: Head of Data Description This role can be filled via fixed term contract or via daily rate (Inside IR35) via umbrella company. Initially 3 months with the potential for expansion. Role Overview This is a focused, high-value engagement to lead the data architecture of Defaqto's redesigned market data model. We have an initial view of the logical structure we need, and we are looking for an experienced architect to test, challenge, and refine that thinking - then translate it into a signed off logical model and implementation recommendations for the CTO and Head of Data to act on. What you'll do Context: We have developed an initial view of the logical architecture - centred on four core entities: Package, Component, Attribute, and Market - but this is a starting point, not a fixed brief. We are looking for an architect who will interrogate that thinking, validate it against real business requirements, and produce a model that genuinely fits how our data needs to work. The initial scope is the market data product estate and the primary research data platform. Technology choices for physical implementation have not been finalised. Google BigQuery is our existing lakehouse platform and the likely foundation, but decisions on the transformation layer, tooling, and overall implementation approach will be made during this engagement in collaboration with the CTO and Head of Data. The logical model itself is a technology agnostic deliverable; implementation recommendations are expected alongside it. The Engagement: This contract covers the design and architecture phase of the data model project (Phase 1 of a phased delivery programme). The primary output is a signed off logical data model and a technology implementation recommendation, produced in close collaboration with the CTO and Head of Data. The logical model is a technology agnostic deliverable; the implementation recommendation should be grounded in Defaqto's existing technology landscape and make a clear case for the chosen approach. A Senior Data Engineer - permanent hire, to be recruited, will own the build and ongoing implementation once the architecture is agreed. The architect's role is to design the model, recommend the implementation approach, and provide sufficient documentation that the engineering team can execute without ongoing dependency on the contractor. Scope & Constraints In Scope Logical model design for the market data product estate - core entities, relationships, and attributes Technology implementation recommendation - physical implementation approach suited to the existing stack, presented to CTO and Head of Data Compatibility view specification for research platform continuity during transition Business rule formalisation for deduplication, ratings hierarchy, and attribute priority logic Stakeholder workshops and sign off facilitation Data dictionary and handover documentation Out of Scope Transformation layer build and implementation (owned by Senior Data Engineer) Research platform frontend adaptation (Phase 2 workstream) Full estate migration beyond the initial market data scope (Phase 2+) Ongoing data governance or catalogue ownership Graph database design or implementation What you'll need to succeed Essential requirements Demonstrable experience leading logical and physical data model design for analytical data warehouses Strong command of entity relationship modelling, normalisation, and dimensional design Experience with cloud data warehouse platforms - Google BigQuery is the existing lakehouse technology; hands on experience with BigQuery or equivalent (Snowflake, Redshift, Databricks) is expected Ability to produce technology agnostic logical models and translate them into well reasoned implementation recommendations Proven ability to facilitate workshops with mixed technical and non technical stakeholders and produce signed off artefacts Experience producing data dictionaries and technical documentation to a standard usable by engineering teams Comfortable presenting architecture options and trade offs to senior technology leadership Ability to work independently and manage delivery to milestone based timelines Desirable requirements Familiarity with dbt - sufficient to design a schema that a dbt based transformation layer can implement effectively Experience designing compatibility or migration layers for legacy platform transitions Exposure to data cataloguing tools (Google Dataplex, DataHub, Atlan) Understanding of product data or market intelligence data structures Experience working within a phased, non big bang migration approach Important to know Location: This is a hybrid working role usually with 2 days each week in the office - office base can be London or Haddenham. From time to time if there are workshops, you may need to be in the office more frequently. Right to Work Applicants must already hold a legal right to work in the UK without time restrictions and without the need for future sponsorship. We are unable to provide Skilled Worker visa sponsorship.

Job Title: SOLUTION ARCHITECT L1 (CONTRACT) Location: London, United Kingdom Job Description We urgently require 2x experienced Snowflake senior designers for a period of 3-4 months. Ideally, these senior Snowflake designers should have delivered complex designs across Snowflake, the data lake, Salesforce, and ACM, including data modelling, data contracts, data mapping, and data export/imports. Must Have Skills and Experience Deep DBT and Salesforce skills with proven use cases. Experience with Python for data engineering and orchestration. Key Responsibilities Engage with Product Owners, Business Analysts, Solution Architects, and platform designers to consult on requirements and estimate end to end delivery. Create platform designs that provide clear traceability back to requirements and solution designs. Design how multiple data feeds from source are ingested into pipelines. Develop mapping documentation aligned with requirements and downstream Snowflake/DBT processes. Transition design into engineering leads for build. Consult and support engineers during build, test, and deployment, providing guidance and solutions. Mandatory Skills Snowflake Equal Opportunity Employer We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, caste, creed, religion, gender, marital status, age, ethnic and national origin, gender identity, gender expression, sexual orientation, political orientation, disability status, protected veteran status, or any other characteristic protected by law. Wipro is committed to creating an accessible, supportive, and inclusive workplace. Reasonable accommodation will be provided to all applicants including persons with disabilities throughout the recruitment and selection process. Accommodations must be communicated in advance of the application, where possible, and will be reviewed on an individual basis.

Wipro Technologies is seeking experienced Snowflake senior designers in London, United Kingdom. This contract position requires two candidates for 3-4 months, focusing on complex designs involving Snowflake, data mapping, and orchestration. The ideal candidates will collaborate with Product Owners and engineers, providing solutions and guidance during the development and deployment phases. Proven expertise in DBT and Salesforce is essential, along with strong skills in Python.

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of 300,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready? About your role Enterprise AI is forcing organisations to rethink their data estates. Data platforms designed mainly for reporting are often not enough for GenAI, semantic search, agentic workflows and AI-enabled decision making. Clients now need data that is trusted, governed, contextualised and consumable by both people and intelligent systems. We are looking for client-facing Enterprise Data Architects to join our growing Enterprise AI practice. You will help clients transform fragmented data estates into AI ready foundations, advising on architecture decisions across cloud data platforms, lakehouse and warehouse patterns, data products, semantic layers, metadata, lineage, governance, knowledge graphs and GenAI retrieval patterns. This is a consulting role, not a purely internal architecture role. You will diagnose ambiguous client problems, shape options, make trade offs explicit, and translate complex data architecture issues into clear decisions for both technical teams and executive stakeholders. You will work in cross functional teams alongside product owners, data scientists, ML and GenAI engineers, data engineers, business analysts and client stakeholders. Typical outputs may include target state architectures, maturity assessments, platform option appraisals, data product designs, governance models, lineage maps, ontology and semantic models, integration patterns, GenAI data readiness assessments and implementation roadmaps. We are hiring across several levels. At earlier levels, we expect strong architecture delivery experience and hands on platform understanding. At senior levels, we expect the ability to shape enterprise data strategy, influence senior stakeholders, lead complex architecture decisions and guide multi disciplinary delivery teams. We do not expect every candidate to be a specialist in every aspect of AI ready data architecture. We are looking for architects with strong core data architecture experience and credible depth in some of the areas that matter for AI enabled data estates, such as governance, semantic modelling, lakehouse architecture, data products, metadata management, knowledge graphs, RAG or enterprise data strategy. Responsibilities Design AI ready enterprise data architectures that enable analytics, AI, ML, GenAI and agentic applications to consume data accurately, securely and with appropriate business context. Assess clients' existing data estates, diagnose structural, governance, semantic and quality issues, and design pragmatic modernisation roadmaps. Advise clients on architecture and platform choices, helping them navigate trade offs between lakehouses, warehouses, data fabrics, graph databases, semantic layers, vector search and hybrid architectures. Define data governance and metadata patterns covering ownership, stewardship, quality, lineage, cataloguing, access control and data lifecycle management. Design data products, data contracts and information models that make enterprise data reusable across analytics, AI, GenAI and operational workflows. Shape semantic layers, ontologies and knowledge graph patterns where these improve data discoverability, interoperability, explainability or AI consumption. Oversee high level design of ingestion, integration and transformation patterns, including batch, event driven and real time architectures. Identify and mitigate data related risks, including poor data quality, weak provenance, data leakage, inappropriate access, retrieval failure and inference time use of enterprise knowledge. Act as a trusted advisor to client stakeholders, translating technical architecture concepts into clear business outcomes, options and risks. Contribute to proposals, client conversations, internal methods and thought leadership on enterprise data architecture and AI ready data foundations. Skills and Qualifications Essential Skills 5-10+ years, depending on level, in data architecture, enterprise architecture, solution architecture or senior data engineering roles. Demonstrable experience designing modern data architectures for analytics, AI, ML or GenAI consumption. Strong understanding of enterprise data architecture patterns, including cloud data platforms, lakehouses, warehouses, data integration, data modelling and metadata management. Experience contributing to or leading data governance initiatives, including catalogues, lineage, ownership, stewardship, data quality and metadata management. Practical understanding of semantic layers, ontologies or knowledge graph concepts, with hands on experience in at least one of these areas. Deep experience with at least one major cloud data platform, such as AWS, Azure or Google Cloud, and familiarity with leading lakehouse or warehouse technologies. Understanding of how data architecture decisions affect AI and GenAI outcomes, including data quality, provenance, context, retrieval, security, privacy and semantic consistency. Familiarity with GenAI data patterns such as retrieval augmented generation, vector search, embedding pipelines, chunking strategies or enterprise search. Strong stakeholder management and communication skills, with the ability to present complex technical trade offs clearly to non technical sponsors and senior executives. Excellent written and verbal communication skills in English. Bachelor's degree or equivalent experience; quantitative, technical or analytical disciplines are an advantage. Willingness to travel, up to around 60% depending on project requirements, across the UK and internationally. Preferred Skills A second major European language is an advantage. Experience with graph modelling, ontology standards or graph query languages such as RDF, OWL and SPARQL. Familiarity with feature store design and MLOps / DataOps pipeline integration. Experience with stream processing at scale using Apache Kafka or Apache Flink. Background in master data management or data mesh architecture. Consulting or comparable client facing delivery experience. Exposure to cloud data platforms (Databricks, Snowflake, Microsoft Fabric, Azure Synapse, Google BigQuery, Amazon Redshift), data engineering and orchestration (Spark, dbt, Airflow, Azure Data Factory, AWS Glue, Dataflow, Kafka, Flink), governance, catalogue and lineage tools (Microsoft Purview, Collibra, Informatica, Alation, Atlan, OpenLineage), graph, ontology and semantic technologies (Neo4j, Amazon Neptune, Stardog, GraphDB, RDF, OWL, SPARQL), or AI/ML data infrastructure (vector databases such as Pinecone, Weaviate, Milvus, Azure AI Search, OpenSearch or pgvector; feature stores such as Feast or Tecton; model lifecycle and experiment tracking tools such as MLflow). We do not expect candidates to have worked with all of them. Personal Attributes Comfortable working in ambiguous consulting environments, shaping options, making trade offs explicit and taking senior stakeholders on the journey from strategy to implementation. Self directed, able to prioritise and juggle multiple workstreams. Clear communicator who can simplify complexity for technical and non technical audiences alike. Collaborative, curious, continuous learner. We offer industry leading compensation and benefits, along with top training and development opportunities so that you can grow your career and achieve your personal ambitions.

Is it Permanent/ Contract: Open for both Is it Onsite/Remote/Hybrid: for London (4 days WFO, 1-day WFH mandatory) Experience 15+ years About the Role We are seeking a senior Data Architect to join the engineering organisation as part of Project Compass. This programme is delivering next-generation capabilities across Accounts (Real-Time Ledger), Payments Engine, and Foreign Exchange - all of which generate, consume, and depend on high-quality, well-governed data at scale. The Data Architect will own the end-to-end data architecture across spanning Snowflake as the enterprise data warehouse and a landscape of in-house application databases (relational, time-series, document, and in-memory stores) that serve real-time operational workloads. You will define how data flows from source systems into the warehouse, how application databases are modelled and managed, and how data products are exposed to downstream consumers within and beyond. This is a hands on, delivery focused role. You will work closely with Integration Architects, platform engineers, and domain product teams to translate business data requirements into durable, governed, and scalable data solutions. Key Responsibilities Data Architecture & Strategy Define and own the data architecture target state, covering the Snowflake enterprise data warehouse, application databases, and the data flows that connect them Establish a unified data modelling standard across relational (PostgreSQL, Oracle), in memory (Redis), time series (TimescaleDB / InfluxDB), and document (MongoDB) stores used by applications Design the data ingestion and movement architecture - real time CDC pipelines, batch ETL/ELT patterns, and event driven feeds from the NATS messaging layer into Snowflake Define data domain boundaries, ownership, and lineage standards aligned with Project Compass product domains (RTL, Payments, FX) Produce and maintain authoritative data architecture artefacts: entity relationship models, data flow diagrams, data dictionaries, and Architecture Decision Records (ADRs) Snowflake & Data Warehouse Lead the design and evolution of the Snowflake data warehouse, including schema design (Raw / Conformed / Consumption layers), virtual warehouse sizing, and cost governance Define standards for data loading (Snowpipe, Streams & Tasks, external stages), transformation (dbt patterns), and data sharing across business units Establish Snowflake data access controls, row level security, dynamic data masking, and PII governance in line with regulatory requirements (GDPR, BCBS 239) Champion Snowflake best practices for performance tuning, clustering keys, materialised views, and query optimisation Evaluate Snowflake native capabilities (Snowpark, Cortex AI, Dynamic Tables) and recommend adoption where they accelerate data product delivery Govern the application database landscape across - reviewing schema designs, indexing strategies, and data lifecycle management across all in house databases Define patterns for operational data stores (ODS) that bridge real time application databases and the analytical warehouse layer Ensure consistency between transactional data models and their warehouse representations, minimising transformation complexity and maximising fidelity Set standards for database change management, migration tooling (Liquibase / Flyway), and schema versioning across the application estate Identify and remediate data quality issues at source, defining data contracts between application teams and downstream consumers Data Governance & Quality Define and implement data governance frameworks covering data ownership, stewardship, classification (PII, sensitive, public), and retention policies Establish data lineage and cataloguing standards, working with tooling such as Apache Atlas, Collibra, or Snowflake Horizon Catalog Design and enforce data quality rules and SLAs at ingestion, transformation, and consumption layers Collaborate with the Risk and Compliance function to ensure data architecture meets BCBS 239 Risk Data Aggregation and Reporting requirements Champion Master Data Management (MDM) principles for shared reference data (counterparty, instrument, currency) across domains AI, Analytics & Data Products Define the architecture for data products - curated, well documented datasets served to analytics, reporting, and AI/ML consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly detection, and limit utilisation forecasting Evaluate and integrate AI assisted data tooling (AI powered cataloguing, natural language querying, automated data quality) where it accelerates productivity Partner with the Analytics Engineering team to establish dbt modelling standards, testing frameworks, and documentation practices Work hands on across multiple product teams as a data authority, balancing strategic design with direct delivery contribution Guide and mentor application engineers on data modelling, query optimisation, and data quality best practices Engage senior stakeholders across Technology, Finance, Risk, and Operations to communicate data strategy, risks, and trade offs Facilitate data architecture working groups with platform, BI, and enterprise architecture teams to align on shared standards Core Technical Skills Data Warehouse Transformation dbt (data build tool) - modelling layers, testing, documentation, incremental strategies Application Databases Data Integration AWS - S3, RDS, Aurora, Redshift (migration context), Glue, Lake Formation, IAM, VPC Data Governance Data lineage, cataloguing (Apache Atlas / Collibra / Snowflake Horizon), GDPR, BCBS 239, MDM AI / ML Data Query & Performance SQL optimisation, clustering keys, partitioning, query profiling, cost based tuning Data Landscape The Data Architect will work across the following technology landscape. Candidates should have direct experience with the majority of these platforms and the ability to define coherent architecture across heterogeneous stores: Platform / Store Primary Use Snowflake Enterprise data warehouse, analytics, reporting, data sharing Oracle DB Migration strategy, data contracts, schema versioning Redis Cache invalidation, persistence strategy, data consistency MongoDB TimescaleDB NATS JetStream AWS S3 / Glue Data lake staging, archival, batch ingestion into Snowflake Partitioning, file format (Parquet/ORC), Lake Formation governance Finance Domain Knowledge Candidates should have hands on data architecture experience in one or more of the following financial services domains: Domain Key Data Concepts Double entry accounting data models, event sourced ledgers, real time balance aggregation, reconciliation datasets Payments Engine Payment message data (ISO 20022 / SWIFT), settlement instructions, payment status lifecycle, fee and charge data Trade data models, rate feeds and time series storage, position keeping, P&L attribution data Exposure data models, limit hierarchy, breach event data, real time risk aggregation feeds Client Onboarding Client master data, KYC / AML data structures, account hierarchy, regulatory reporting feeds Regulatory Reporting BCBS 239 data lineage, EMIR / MiFID trade reporting data, data quality SLAs for regulatory submissions Experience & Profile 15+ years of progressive technology experience, with at least 5 years in senior data architecture roles Deep, hands on experience with Snowflake as an enterprise data warehouse - ideally holding Snowflake SnowPro Core or Advanced: Architect certification Proven track record of designing data architectures across heterogeneous application database landscapes in large financial institutions or fintech organisations Demonstrated experience implementing data governance frameworks, lineage tooling, and data quality programmes at programme scale Comfortable working hands on - writing dbt models, reviewing SQL, profiling queries - while operating at senior stakeholder and architecture level Experience with CDC based real time data pipelines and event driven data integration patterns Strong communicator able to convey complex data architecture decisions to both engineering teams and business stakeholders Familiarity with AI/ML data architecture patterns (feature stores, vector databases, LLM data pipelines) is a strong advantage AWS Solutions Architect or AWS Data Analytics certification is advantageous.

Salary: £48,000 - 60,000 per year Requirements Extensive experience in Snowflake. Excellent skills in SQL, Python, Data Modelling, and Data Transformation. Strong knowledge of AWS, PowerBI, and CI/CD. Experience with GIS is desirable. Responsibilities Design, build, and maintain high-quality pipelines and models in Snowflake. Translate defined data architecture and standards into implemented solutions. Develop robust ELT/ETL pipelines using DBT and workflow/orchestration tools. Apply data quality checks, lineage tracking, and security standards across data projects. Technologies AWS CI/CD ETL GIS Python SQL Security Snowflake dbt Cloud More We are offering a contract position at £450 per day, inside IR35, for a duration of 3 months. The role requires working 1-2 days per week in Oxfordshire, with an immediate start.

Ready to make travel easier for millions? Airalo is the world's first and largest eSIM store, helping travellers stay connected seamlessly in over 200 countries and regions. We trust our teams to take ownership, put customers first, and do work that has a real impact every day. What's in it for you? Airalo offers team members a range of perks, including remote work, generous PTO, wellness and learning allowances, and, of course, our annual Airalo Away retreat. Learn more about our benefits here; Hi, I'm Andra, Director of Data at Airalo! Our team works across the full data ecosystem, from collection to insights activation, ensuring that every piece of data drives meaningful action. We're curious problem-solvers who love tackling challenges that haven't been solved before and building tools and processes that scale impact across the company. Airalo's fully remote Data team is growing. You'll turn numbers into decisions that shape the future of our business, collaborating with cross-functional teams to solve complex problems and influence how millions of travellers stay connected. This isn't just dashboards - it's using data to drive strategy, inform product and growth decisions, and create real impact. You'll have access to best-in-class tools, the freedom to experiment, and a team ready to turn insights into action. As the Data Engineering Manager, you will lead the foundational backend of our data organization. You will directly manage our current pod of Data Engineers (2 Senior Data Engineers and 1 Customer Data Platform Engineer) and shape the hiring roadmap as the function grows - including scoping future specialized roles such as Machine Learning Engineers. Partnering closely with the Data Director, you will help us transition out of the reactive, ad-hoc phase and into a structured, highly scalable data ecosystem. You will own the architecture, ingestion, and orchestration that powers the rest of the data team - ensuring that our Analytics Engineers, Data Analysts and other users have a rock-solid, high-quality foundation to build upon. This role goes beyond building a data platform. You'll be the connective tissue between Product & Engineering, MarTech, and our partner ecosystem - ensuring data is produced cleanly at the source, captured reliably, and delivered cohesively across the entire organization. What You Will Do: Manage, mentor, and grow a high-performing team of Senior Data Engineers and CDP Engineers. Drive hiring for the Data Engineering function as it grows, including scoping future specialized roles such as Machine Learning Engineers. Foster a culture of engineering excellence, continuous learning, and cross-pollination of knowledge. Own the technical roadmap for Airalo's data infrastructure (GCP, BigQuery), orchestration (Dagster, Airflow), and ingestion (Fivetran, custom APIs). Drive data-platform architecture decisions, turning ambiguous business problems into scalable, production-grade technical designs. Bridge the data platform with MarTech and third party ecosystems (PSPs, MNOs, CDPs, attribution platforms), ensuring customer events, campaign data, and partner integrations flow cohesively in both directions. Partner with Software Engineering to embed data quality at the source - implementing data contracts, co owning schema decisions, and driving the rollout of a data catalogue across the organization. Establish the foundations for real time data capabilities as the business matures beyond batch processing. Design systems that prioritize data quality, privacy, and governance standards across all data initiatives. Transition the team's workflow from reactive problem solving to structured, agile delivery. Oversee the maintenance and optimization of high performance data pipelines, implementing CI/CD automation, observability frameworks, and strict data quality gates. Roll up your sleeves when necessary to assist with complex code reviews, Python/Scala development, or unblocking the team on difficult architectural challenges. Act as a strategic partner to the Analytics Engineering Manager and Data Director to build the backend requirements necessary to achieve our company wide goal of 80 % self serve analytics. Must-haves: 7+ years of professional experience as a Data/Software Engineer, with at least 2+ years of experience directly managing and scaling data engineering teams. You thrive in low maturity or greenfield data environments. You're comfortable navigating ambiguity and enjoy the process of laying down paved roads and engineering standards where none existed before. Deep, hands on background with major cloud platforms (GCP preferred) and cloud native data warehouses (BigQuery preferred, or Snowflake/Redshift). Strong experience with orchestration tools (Airflow, Dagster), ELT pipelines (Fivetran, dbt), and distributed data processing frameworks (Apache Spark, Flink). Hands on experience using AI tools to accelerate engineering workflows - code generation, code review, pipeline debugging, or documentation. Strong coding experience in Python (and/or Scala) and advanced SQL across relational and non relational databases. Experience implementing CI/CD, Infrastructure as Code, and observability/monitoring for data pipelines. Bachelor's degree in Computer Science, Engineering, Statistics, Information Systems, or a related quantitative field. Nice-to-have: Experience implementing data contracts, data catalogues (Atlan, Amundsen, DataHub), or federated governance models. Experience with Customer Data Platforms (Segment, mParticle, or similar), MarTech data integration, and real time event processing. Experience in marketplace, B2C, or high volume transactional businesses. Previous work in globally distributed data environments (multi currency, multi region, multi language). Experience building or contributing to experimentation platform infrastructure (A/B testing pipelines, feature flag data, experiment analysis frameworks). Exposure to Machine Learning infrastructure - not necessarily building models, but scoping teams, tooling, and pipelines that support ML workloads. If you are interested in this position, please apply via the link. Please note that to be considered for this role, you must reside in and be fully eligible to work in either Romania, Spain, or the UK. Proof of a valid right to work in one of these three countries will be required. By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process.

Job Summary As the Senior Data Platform Engineer in the Cyber Data Platform team, you will play a key role in building and maintaining a robust data platform that enables users to develop advanced analytics, machine learning, and GenAI solutions to strengthen our security defences. You will collaborate closely with cross functional data teams to ensure the platform is scalable, secure, and aligned with cybersecurity goals, contribute to the data platform architecture, and mentor junior members. Responsibilities Data Architecture - Design, build and manage real time, near real time and batch data architectures that support threat detection, incident response and reporting through advanced analytics, machine learning and GenAI capabilities. Data Integration and Transformation - Implement and manage automated frameworks for integrating data from various security sources into the security data lake and for moving data between raw, trusted and curated data layers. Coding - Contribute to raising the team's code quality by producing high quality code, conducting thorough peer reviews, and providing constructive feedback. Automation and DevOps - Implement various automations and DevOps practices to streamline the deployment, configuration and management of data platform components. Collaboration and Communication - Collaborate with teams from various departments, communicating technical concepts and solutions to stakeholders with diverse technical expertise. Recruitment & Talent Development - Support the ongoing recruitment and talent development process for the cyber data team. Key People and Teams Members of the cyber data platform team (Engineering Managers, Product Managers, Data Platform, Analytics and Machine Learning Engineers) Members of the broader security team (Product Managers, Security Managers, Security Engineers, Security Testers, Security Analysts and Risk & Compliance team members) Security Stakeholders across Tesco Operational Skills Strong communication skills, both written and verbal, to engage with team members and stakeholders. Strong analytical abilities to empower users with self service capabilities through the data platform. Experience with collaborative development methods such as mob or ensemble programming. Qualifications and Experience Solid programming experience with Python and proficiency in SQL. Experience building data platforms on cloud services such as Databricks on Azure or GCP BigQuery, and big data technologies like Spark or Flink. Solid grasp of Kubernetes, CI/CD and Terraform. Working knowledge of ETL and ELT frameworks and orchestration tools such as Airflow and dbt. Ability to provide clear input, guide and empower junior team members to achieve desired outcomes. Familiarity with machine learning and AI tools is desirable. Knowledge of cybersecurity principles and practices. Benefits Financial & Reward Benefits Annual bonus scheme Retirement savings plan - save between 4% and 7.5% with Tesco matching your contribution. Life Assurance - 5 contractual pay. Share Schemes - Join our Buy As You Earn & Save As You Earn share schemes after 3 months of service. Holiday & Time Off Holiday starting at 25 days plus a personal day, plus 8 Bank holidays. Health & Wellbeing On site gym at our Welwyn Campus with discounted Gympass membership & free health checks via Nuffield Health. 50% off health checks at Tesco Pharmacy. Employee Assistance Programme to help you deal with life's challenges. Colleague Clubcard & Discounts Colleague Clubcard, including a second card for a family member, after 3 months of service. Additional Benefits Exclusive deals and discounts website saving you money on everyday purchases, treats for the family, eating out and utility bills. Cycle to work scheme. Shuttle Bus Service to/from Welwyn Garden City Station to Welwyn Campus. Opportunities to gain learning and award winning training to help you achieve the job and career you want. Financial wellness support from partnered experts. Participation in fundraising activities with long term charity partners.

We're on a mission to make real estate transactions smarter, faster, and friction-free. Real estate is the world's largest asset class, yet the legal processes and tools behind it remain slow, manual, and underinvested. Lawyers must review dense documents line by line and piece together information across silos, all while clients demand faster, more transparent due diligence. That where we come in. Orbital Copilot is the AI assistant built exclusively for commercial real estate law. Developed with former practicing real estate lawyers, it accelerates complex due diligence by up to 70% while delivering legal-grade precision. We've just raised a $60m Series B to accelerate our UK/US expansion. We're trusted by leading firms like Goodwin and BCLP to remove the busywork so legal teams can focus on what they do best: applying sharp legal judgment, delivering standout client service, and getting deals over the line faster. Working at Orbital means joining a team that's reimagining how real estate transactions get done - moving fast, working collaboratively, and giving people the ownership to make a real impact from day one. Role Overview This is a solo greenfield build one engineer, Postgres source, 31 July launch. We're looking for a Senior Data Analytics Engineer (Contract) to design and build the analytics foundations for a new greenfield product. There is no existing infrastructure: no pipelines, no operational data store, no semantic layer. You are starting from zero and leaving behind something clean, well documented, and extendable. The core challenge is architectural: taking a live Postgres product database as the source of truth, understanding how to extract from it reliably as its schema evolves, standing up well structured operational data stores, and making sound decisions about where data lives, how it flows, and how it is queried. The analytics and visualisation layer, internal dashboards for engineering, product, and CS teams, plus customer facing usage reporting for law firm clients, sits on top of those foundations and is equally in scope. This is a Senior role because you are leading this build independently. Ciaran (Head of Product Engineering) is your day to day contact and sounding board, but he is not a data engineer and will not be directing the technical work. The architecture, the tooling decisions, and the quality of what gets built are yours to own. This is an AI first environment. We use Claude Code and coding agents extensively. Good documentation here means documentation written for a coding agent: how to access systems, how to extend pipelines, why decisions were made. That is the handover standard. What this role is not We are not looking for someone who will build an overblown lakehouse. We are not looking for a pure analytics or BI engineer who is great at SQL and dashboards but cannot stand up cloud infrastructure independently. And we are not looking for someone who needs a surrounding data team or close technical direction to operate. The right person is a senior builder: self sufficient, architecturally minded, and pragmatic enough to build something clean that a coding agent can extend after they leave. What you will be doing Assess the Postgres product database and design an analytics architecture appropriate for our current scale: operational data stores, extraction strategy, schema isolation, and semantic layer, without over engineering. Build reliable extraction pipelines from Postgres and other operational sources that are resilient to schema drift and isolated from the application layer. Design and implement a well structured operational data store: clean schemas, stable marts, and a semantic layer that teams across the business can query and trust. Define canonical business metrics: product usage, customer health, LLM token and cost telemetry, document volume, workflow adoption, latency, and engineering KPIs, and make them consistently available across the business. Stand up internal analytics for engineering, product, CS, and leadership, and customer facing usage dashboards for law firm clients showing their own usage and cost data. Evaluate and recommend tooling for transformation, the BI and semantic layer (Omni Analytics is being evaluated alongside Metabase), and cloud infrastructure: bring your own experience and opinions. Set up secure data access, scheduled jobs, object storage, secrets management, monitoring, and cost aware infrastructure in AWS or Azure independently. Establish data quality checks and pipeline observability from the start. Write documentation for AI coding agents: how to access, understand, and extend the systems you build, with context on the decisions you made. Attend daily standup and work closely with Ciaran throughout, with a clean handover at the end of the engagement. You should apply if You have led or owned the architecture of a data platform: you have made the decisions on how data flows, where it lives, and how it is accessed, not just executed a design handed to you. You have extracted from a live operational relational database (Postgres is ideal) and dealt with schema drift in production. This is the core of the technical challenge and the experience that matters most here. You can independently set up a cloud data environment in AWS: data access, scheduled jobs, object storage, secrets, monitoring, and cost controls, without needing a platform team around you. You have built a data platform from scratch or near scratch before and can describe the decisions you made at the start. You are strong in both data engineering (pipelines, infrastructure, operational data stores) and analytics engineering (semantic layer, metric definitions, clean queryable data models). You have deep SQL and data modelling capability: schema design, mart design, and semantic layer definition from scratch. You understand BI and semantic layer tooling (Omni Analytics, Looker, Metabase, Cube, or similar) and can make a justified recommendation. You are pragmatic about tooling: you will not reach for a full lakehouse or managed warehouse when something lighter and more maintainable serves the purpose. You write documentation that a coding agent can act on independently, not just a README for a human. You are available to start by 1 July 2026. It would also be great if you have Experience building customer facing or embedded analytics in a B2B SaaS product. Experience instrumenting AI/LLM usage: token counts, cost tracking, latency, and evaluation datasets. Familiarity with data residency requirements we have strict UK/EU and US data residency obligations. Experience in ISO 27001 or SOC 2 compliant environments. Experience with multi tenant reporting, row level security, and customer data isolation. Startup or early stage background. Experience with transformation tooling such as dbt or equivalent code first approaches. Security is everyone's responsibility at Orbital. We ask all team members to follow our security policies, complete regular awareness training, and handle sensitive data with care in line with ISO 27001 standards. Spot something unusual? Reporting risks or incidents quickly helps us maintain the strong culture of security and compliance we all depend on. At Orbital, we're committed to building a diverse and inclusive team. We especially welcome applications from people who are traditionally underrepresented in tech. Even if you don't meet every single requirement, or if the right role isn't listed yet, we'd still love to hear from you. This hiring range is a reasonable estimate of the base pay range for this position at the time of posting. Pay is based on several factors, which may include job related knowledge, skills, experience, and business requirements.

As a Senior Product Analyst, you'll own how we measure success, shape the frameworks that guide product decisions, and lead others to embed data driven thinking across our product teams. You'll move seamlessly from strategic thinking to hands on delivery; defining scalable frameworks to drive experimentation maturity and product measurement, partnering with a range of stakeholders to turn insight into meaningful business impact, and coaching others to raise the bar on how we use data to learn fast and scale what works. You'll be a trusted partner to not only Product, Engineering and Marketing, but also our Commercial & Account Management teams- influencing decisions through clarity, storytelling, and commercial insight-living our 'Better Together' value. Reports To: Head of Product and Marketing Analytics Contract Type: Permanent Location: UK Remote (Travel to Richmond, London office around once a month) What You'll Own (The Impact) Fuel the Momentum: Analyse product performance; moving beyond typical funnel metrics, into advanced segmentation, propensity modelling & cohort analysis. You'll identify pain points and opportunities - making valuable recommendations. You don't wait for a ticket; you proactive find opportunities to deliver insight. You'll leverage funnel forensics to pinpoint friction and leakage in the user journey, and develop our behavioural analytics capabilities to understand how users interact with features and what actions drive conversion. Progress over Perfection: Run A/B tests and experimentation outcomes, to get real world data and iterate fast- You'll partner closely with Product & Technology to ensure the optimal balance of rigorous experimentation practice, whilst maintaining release velocity. You'll develop robust hypotheses, conduct pre/post analysis, and bring statistical rigor to the experimentation process. Fearless Storytelling: Use SQL (Databricks via DBT), Power BI, and Google Analytics to translate complex data into clear, persuasive stories & recommendations. You'll be expected to speak up in the room, even if the data tells a tough story. The tools are how you'll get the data, but your story telling abilities will provide the crucial "so what?". Build the Baseline: Help maintain our data taxonomy and event tracking standards. You'll ensure our data is clean so our decisions can be "bold." Beyond governance, you'll act as a domain expert across our digital tooling suite: advising on tagging requirements, event tracking implementation, and attribution; partnering with Engineering to ensure our instrumentation keeps pace with product development. Smash Silos: Partner with Product Managers to validate hypotheses and size opportunities. We win when the whole team succeeds. You'll become a trusted member of the team(s) that you support- becoming a consultative subject matter expert where your voice is as valuable as your insights. Make it self serve: Build, either yourself or with specific BI & Analytics colleagues, data products that empower stakeholders to investigate and answer their own questions. You'll provide guidance, governance and training to raise & maintain the standards for data fluency. The goal is a data literate product organisation, not an Analytics Team bottleneck- freeing your time for deeper insights. What You'll Bring A Challenger Mindset: You are allergic to 'how it's always been done around here' and prefer to ask 'Why?' Technical Foundations: Proficient SQL skills and experience with visualization tools (Looker, Power BI), web analytics (GA, Amplitude). Analytical Grit: You have the resilience to handle honest data and the curiosity to dig deeper when a plan isn't working. Commercial Awareness: Confident operating autonomously in a scaling environment, balancing detail with commercial context. Dynamic Spark: You bring a restless energy and a genuine desire to help us become the undisputed challenger in the UK used car Classifieds marketplace. Perks & Benefits Financials We offer an annual bonus scheme or commission plans for our Commercial team. We more than match your commitment to your pension, so when you contribute 6%, we put in 9%, taking your total up to 15% of your base salary. Quarterly value led awards with generous cash prizes. Referral Bonus: Recommend a colleague, get £2,000. Work-Life 25 days (plus bank holidays) Hybrid role, two days a week based in our Richmond office Family Enhanced leave after 6 months of service: Maternity/Pregnant Parent Leave: 20 weeks at 100% pay. Paternity/Non-birth Parent Leave: 12 weeks at 100% pay. Volunteer Days: We offer 2 volunteer days a year so you can help out wherever matters to you. Health & Peace of Mind AXA Private Healthcare: High-level coverage for you, partners, and dependents-including pre existing conditions. Bupa Dental: Level 2 coverage for cashback on preventative, restorative and emergency care. Private GP: 24/7 digital access via Income Protection: 13 weeks of sick pay, before going onto Long term Illness cover with Canada Life Life Assurance: 4x basic salary covered by Unum. Specialist Support: Free counseling and menopause/fertility support via Peppy. Your Growth Learning budget and continuous development opportunities. Every manager has a dedicated budget for your specific role development. The Extras Your choice of a MacBook or Windows laptop. : Discounts at over 30,000 retailers and entertainment venues. Annual conference with top tier industry guest speakers. Past guests include names like Matthew Syed and Damian Hughes. Whether it's our Summer bash or the annual festive party, we make sure we take the time to bring everyone together and celebrate in style. Free food & drinks in the office. We're proud partners of Brentford FC, and we share the rewards with you. From tickets to matches to the bucket list opportunity to actually play on the pitch yourself, we bring you closer to the action. Diversity & Inclusion at Cazoo & MOTORS The best ideas come from people with different backgrounds, experiences and ways of thinking. At Cazoo we are a place where people feel comfortable speaking up, contributing and growing. Bring your perspective. Bring your experience. Be yourself.

Work mode: Fully onsite 5 days WFO/week. Contract duration: 1 year. Location: Basildon, UK. Client: Fiserv. Job Details Role Title: Snowflake Data Engineer Job Description Hire a senior individual contributor with strong hands on Snowflake experience and a background in production grade data platforms supporting analytics or risk use cases. Prioritize candidates with real AWS production exposure, particularly in environments running data pipelines at scale-hands on experience is favored over certifications. Ensure practical experience with event driven or message based data pipelines, such as Kafka and/or Amazon SQS, used in real time or near real time processing. Focus on candidates who have scaled and optimized existing data platforms, rather than only building greenfield solutions. Assess strong SQL competency and data modeling depth, including experience working with dbt and CI/CD driven data workflows. Role Summary We are looking for a Risk & Data Engineer to design and scale data pipelines, analytical models, and fraud intelligence capabilities that power our MRV/MRD platforms. This role sits at the intersection of data engineering, risk analytics, and platform scale, with a strong focus on Snowflake based data warehousing, rule driven detection, and explainable risk outcomes. You will work closely with product, backend, and platform teams to enable real time and batch fraud detection, regulatory reporting, and multi regional data readiness. Core Responsibilities Design and develop Snowflake based data models to support fraud detection, monitoring, and regulatory reporting. Build and optimize ETL/ELT pipelines using Snowpipe, Streams, Tasks, and stored procedures. Partner with risk stakeholders to support rule based and analytical fraud logic. Ensure data quality, lineage, and auditability across MRV/MRD workflows. Tune SQL performance and optimize warehouse cost and usage. Support experimentation with advanced analytics and GenAI driven insights. Collaborate with platform and backend engineers on end to end data flows. Required Skills & Experience 4+ years of hands on experience as a Snowflake developer, including data modeling and transformation workflows (dbt preferred). Strong expertise in advanced SQL, performance tuning, and warehouse optimization. Hands on experience building ETL/ELT pipelines using Snowpipe, Streams, Tasks, and stored procedures. Experience working with CI/CD and version control (GitHub and/or AWS/Azure DevOps) for data pipelines. Solid understanding of data engineering principles, including data quality, lineage, and monitoring. Exposure to fraud, risk, or compliance analytics, or other rule driven analytical systems. Familiarity with Python or Java for data processing or integration use cases. Required Personal Skills Strong communication skills both verbal and written. Capable of collaborating effectively across a variety of IT and Business groups, across regions and different roles. Good customer service skills. Ability to deal with difficult situations/individuals gracefully. Preferred / Nice to Have Experience modeling data from SAP ECC / SAP S/4HANA or other enterprise systems. SnowPro Certification. Experience with GenAI enabled analytics or feature engineering.

Data Engineer 6-Month contract - Inside IR35 - up to £500 per day London based - hybrid working - 3 days a week onsite Asset Management sector Core Role Overview This is a hands on Data Engineer position working on large scale data platforms within a financial services environment, focused on building, optimising, and deploying scalable data solutions. The role requires someone who can operate across engineering, delivery, and stakeholder engagement - not just a technical coder. Key Skills (Must-Have) Strong SQL development capability Experience with: Azure Data Factory DBT Python Proven experience with: Snowflake development Strong experience working with: Large-scale datasets Performance tuning / optimisation DevOps exposure: Azure DevOps Octopus Deploy Git / source control Ability to: Design, build, and deliver well-structured, testable solutions Work directly with senior stakeholders Desirable / Nice to Have Financial Services / Asset Management experience .NET and Azure development exposure Agile delivery experience Full SDLC understanding Experience with test automation (e.g. TDD) Ability to balance: Short-term delivery vs longer-term strategic build

Advanced Resource Managers Ltd is seeking a Data Engineer for a 6-month contract based in London with hybrid working. The role involves building, optimising, and deploying scalable data solutions in the Asset Management sector. Ideal candidates will have strong SQL development skills, experience with Azure Data Factory, DBT, and Python, as well as exposure to DevOps tools like Azure DevOps and Octopus Deploy. This position requires someone who can engage with senior stakeholders and balance short-term delivery with longer-term strategy.

Togather are the team at the heart of great events. We're a founder-led company of 50+ event specialists working across some of the largest and most exciting events in the UK. Our Marketplace supports both B2B and B2C customers to handpick standout suppliers across street food, drink and venues for private events, from large-scale summer and Christmas parties to regular office lunches for clients including Spotify, Netflix & BBC. Live partners with organisers of large-scale public events, using our 360 tech and industry expertise to curate and deliver exceptional food and drink experiences that also drive commercial results for our clients. From major festivals, stadium fanzones and cultural celebrations, we work hand in hand with client teams to deliver exceptional guest experience for the likes of GALA festival, Rock Oyster, Hill Dickinson Stadium and Pride in London. Internally, we're proud to have been recognised by Tempo and the Startups 100 Awards as one of the UK's best places to work. We care deeply about building an ambitious, supportive and high-performing team. We started life 10 years ago as Feast It, a two-person marketplace launched from a kitchen table, and today, over 10 million guests a year attend a Togather-powered event. Across every project, our mission remains the same: To make events better for everyone. The Role This is a senior individual contributor role, for someone who enjoys building reliable data foundations, turning messy business questions into clear models, and helping teams make better decisions. You'll work closely with Engineering, Product, Commercial, Marketing and Customer-facing teams, reporting to the Chief Technology Officer. The role sits at the intersection of analytics engineering, business insight and modern AI-enabled tooling. We're not looking for someone who only builds reports. We're looking for someone who can improve the way data is modelled, trusted, accessed and used across the business - by people, dashboards, internal tools and emerging AI workflows. You will: Help design, build and maintain the core data models that teams rely on day to day. Improve self-serve analytics (You'll help teams get faster, clearer answers from data without always needing bespoke analysis.) Support customer and supplier journey insight (You'll help us understand how customers and suppliers move through Togather's marketplace, where journeys are working well, and where they can be improved.) Build data products for people and AI tools (We're increasingly using AI tools to help teams work faster and make better use of company knowledge. This role will help make sure those tools are built on reliable, governed and well-modelled data.) Work closely with stakeholders (You'll be a senior partner to teams across Togather, helping them understand what data can and can't tell them.) We'd love to hear from you if you have strong analytics engineering experience and enjoy working in a fast-moving commercial environment. You'll likely have: Advanced SQL skills and strong experience building analytical data models Strong dbt experience, including tests, documentation and maintainable project structure Experience with a cloud data warehouse such as BigQuery, Snowflake, Redshift or Databricks A good understanding of data quality, data contracts and how to prevent downstream reporting issues Experience with at least one BI tool Strong commercial awareness and the ability to connect data work to business outcomes Experience delivering end-to-end analytics projects, from scoping through to delivery and stakeholder communication Clear written and verbal communication skills The ability to explain complex data concepts simply A proactive, independent working style with strong ownership Curiosity about how AI tools can use structured, trusted data safely and effectively These aren't essential, but would be useful: Experience in a marketplace, ecommerce, SaaS or similarly data-rich business Experience modelling supply, demand or customer journey data Experience with product analytics tools such as Segment, GA, Mixpanel or similar Familiarity with privacy, sensitivity tagging or access-control patterns Experience with semantic search, embeddings, vector stores or retrieval-augmented generation Experience working with LLM-powered tools such as Claude, ChatGPT or similar Experience with event-driven ingestion pipelines or reconciliation workflows Generous holiday allowance; 25 days (including a Christmas Closure) + bank holidays Enhanced Pension through salary sacrifice Partnership with Benefits Platform Mintago; EAP service, Workplace Nursery, Cycle to work scheme, Electric car scheme, Health services, Mental Health services, Gym discounts, retail discounts and much more Partnership with Code app: Significant discounts in a lot of London's best restaurants, bars and more Enhanced Mat & Pat leave Free coffee, beer, pizza and an overly stocked snack cupboard in the office Regular team socials and events (including 6 weekly Town Halls with companywide socials & 1 Away day a year) A shiny new MacBook to work on Loads of invites to food-industry events (yes they do usually have free food) Dog-friendly office Training and certification (Trailhead Superbadges, ADM-201, AI/automation conferences) covered via the L&D budget