Data Engineer

• Define and maintain the enterprise data architecture, including target-state designs, roadmaps, and architectural standards and patterns.
• Own the architecture of our Databricks Lakehouse platform, including workspace design, Unity Catalog structure, medallion architecture, and environment strategy.
• Design and govern integration patterns for sharing data with external clients and third parties, including secure, scalable approaches using Databricks Delta Sharing, APIs, and file-based exchange where appropriate.
• Lead the design and adoption of Master Data Management (MDM), including entity definitions, golden-record strategy, match-and-merge rules, and stewardship processes.
• Establish standards and practices for optimising Databricks performance and cost — cluster and compute strategy, Delta table, caching, and workload right-sizing.
• Define data modelling standards (conceptual, logical, physical) across analytical and operational domains.
• Work with data governance colleagues to embed data quality, lineage, cataloguing, classification, and access-control policies into platform design.
• Ensure architectures meet security, privacy, and regulatory requirements, including GDPR and data residency considerations.
• Review solution designs, provide architectural assurance, and support engineering teams through design authority and peer review.
• Design data architectures that enable AI adoption — ensuring data is discoverable, well-governed, and AI-ready for machine learning, GenAI, and agentic use cases across the business.
• Partner with AI/ML teams to define patterns for feature engineering, model data pipelines, vector search, and the safe exposure of enterprise data to AI systems.
• Evaluate emerging technologies and make pragmatic build/buy/adopt recommendations, including data and AI enablement opportunities.

Enterprise Data Architect

• To architect robust data ingestion streams for real time data processing, marketing technology and analytics
• Contribute to the platform logical and physical data models
• Develop ETL, ELT routines for structured analytics
• Develop a range of integrations to APIs, flat files and other external systems to support broader ecosphere
• Work with software developers to enhance gaming platform integration
• Support testing and deployment
• Develop automated monitoring, fault recovery and diagnosis
• Document output to a high level
• Mentor and train localised application support specialists
• Lead the development of AWS data solutions
• Lead adoption of new integration and data technologies
• Input into the AWS technology roadmap and strategy
• Champion best practice and standardisation of development
• Deliver best in class solutions in terms of robustness, recovery and resilience
• Deliver continuous improvement to development methodologies and automation

Senior Data Engineer

• Designing and building scalable data pipelines that ingest healthcare data from multiple providers into trusted research environments and data platforms.
• Developing and maintaining data transformation logic in Python to create high-quality, curated and research-ready datasets.
• Contributing to complex, shared codebases while following engineering best practices including code reviews, testing and clean coding standards.
• Collaborating with data scientists, epidemiologists, software engineers and product teams to understand requirements and deliver impactful data solutions.
• Processing large-scale healthcare datasets and implementing robust data quality, validation and governance controls.
• Transforming and harmonising healthcare data into common data models such as OMOP and FHIR to support research and analytical use cases.
• Creating reusable, scalable and maintainable data products that enable efficient consumption by multiple stakeholders.
• Communicating effectively with technical and non-technical stakeholders to translate complex requirements into practical engineering solutions.
• Producing clear and comprehensive technical documentation covering data pipelines, transformation logic, architecture and operational processes.
• Supporting the design, scoping and implementation of data flows across the wider healthcare data ecosystem.
• Leveraging cloud and big data technologies, including Azure, Databricks, Spark and Data Lakes, to deliver high-performing data solutions.
• Adopting and promoting data engineering best practices, healthcare data standards and continuous improvement across the team.
• Keeping abreast of emerging trends, technologies and standards within healthcare, research and data engineering to drive innovation and excellence.

• Perform exploratory data analysis on a range of complex business problems.
• Interpret business processes into data requirements.
• Define and enforce key data attribute governance strategies.
• Act as geographical data leader, reporting directly to the Data Architecture Manager.
• Collaborate on data team initiatives impacting Ontic’s global strategic pillars.
• Administer and maintain the Snowflake Data Warehouse.
• Devise and maintain data engineering development standards in line with best practice.
• Contribute to data pipelines that clean, transform and aggregate data from disparate data sources into reporting data stores.
• Provide input on the company data strategy by suggesting and proving new technologies and innovations.
• Contributing to the translation of data into valuable insights that inform data driven decisions.
• Develop dashboards and reports to present data insights to stakeholders around the business.
• Support end-user technical questions and assist in data education.
• Host on-site data quality clinics.
• Participate in and audit data governance activities.

• Lead the modernisation and transformation of Newsquest's data platform and supporting architecture, creating a scalable, secure and sustainable foundation for future growth.
• Define and deliver a roadmap for data migration, integration, governance, reporting and analytics capabilities.
• Lead the implementation of a modern data platform, including the development of a data warehouse, data lake, lakehouse or equivalent cloud-based solution.
• Work with stakeholders across the business to understand requirements and translate them into practical data solutions that deliver measurable business value.
• Collaborate closely with IT teams, data engineers, system owners and third-party suppliers to ensure successful project delivery.
• Manage programme plans, budgets, risks, dependencies and resources across multiple workstreams.
• Establish and embed robust data governance, ownership and quality standards across the organisation, increasing confidence and trust in business data.
• Lead and support internal data engineering resources, ensuring successful delivery of platform objectives.
• Drive platform adoption across the business, improving accessibility to trusted data and reducing reliance on manual processes.
• Oversee post-implementation stabilisation, optimisation and continuous improvement activities, ensuring the platform continues to evolve alongside business requirements.
• Identify future opportunities to enhance reporting, analytics, automation and data-driven decision-making.

Data Platform Lead

• Define target-state finance data architectures for clients
• Establish finance data modelling standards
• Design chart-of-accounts, dimensional, and master-data structures
• Map and integrate finance source systems into governed, analytics-ready models
• Design finance data foundations for applied AI/ML
• Set patterns for secure, compliant finance data platforms
• Provide architectural direction for cloud data platforms
• Define the data lineage and controls that support responsible production AI
• Translate ambiguous business and client problems into clear architectural decisions
• Own key technical trade-offs and communicate them clearly

Finance Data Architect

• Develop conceptual, logical, and physical data models for operational, analytical, and regulatory workloads.
• Create and maintain data architecture blueprints and reference architectures covering ingestion, integration, storage, lineage, and consumption.
• Define modelling patterns (3NF, dimensional/star, Data Vault, canonical models) and guide teams on when and how to apply them.
• Optimise physical designs for performance, scalability, cost and resilience across cloud data platforms (e.g., Snowflake, Databricks, Synapse, BigQuery).
• Lead design reviews, ensuring models are accurate, high-quality, and aligned with business capabilities and domain boundaries.
• Define data ownership, stewardship models, and contribute to the governance operating framework.
• Build and maintain data dictionaries, business glossaries, critical data elements (CDEs) and metadata standards.
• Ensure all data solutions align with governance policies, including lineage, retention, access, and security requirements.
• Support governance forums and collaborate with business stewards to drive consistent definitions and controlled change.
• Embed data quality rules and dimensions (completeness, timeliness, accuracy, uniqueness, validity, consistency) across ETL/ELT and streaming pipelines.
• Design data quality metrics, alerts, and monitoring frameworks to surface quality issues to stewards and downstream consumers.
• Partner with engineering teams to implement automated DQ checks, profiling, and remediation patterns.
• Ensure DQ scoring and lineage are built into architecture in a systematic and reusable way.
• Lead architectural discovery to capture business needs, translate them into data requirements, and shape programme/solution scope.
• Manage and communicate architectural decisions with senior business and technical stakeholders.
• Navigate ambiguity and stakeholder nuance, ensuring alignment across product teams, SMEs, vendors, and governance bodies.
• Produce high-quality design documentation and present designs to Architecture Review Boards or equivalent governance forums.
• Oversee the implementation of data architectures and ensure engineering teams follow patterns, standards, and best practices.
• Provide technical guidance on integration design, ingestion patterns, transformation methods, caching, orchestration, and storage optimisation.
• Conduct design assurance throughout delivery, ensuring solutions adhere to non-functional requirements (performance, availability, resilience, cost).
• Coach engineers, analysts, and stewards on modelling, data quality, and governance practices.

Data Architect – 24 month FTC

• Leading the design, development, and implementation of scalable, high-performance data solutions on Azure and Databricks.
• Defining and driving data strategy, data governance, data quality, and platform best practices.
• Optimising platform runtime performance and managing overall cloud costs, with a strong focus on Databricks streaming workloads.
• Providing end-to-end technical leadership, from solution architecture through delivery and production support.
• Collaborating with business stakeholders to understand requirements and translate them into robust technical solutions.
• Demonstrating strong ownership, accountability, and stakeholder management skills.

Technical Lead – Azure Databricks Data Platform

• Provide early delivery design assurance, translating High Level Designs (HLDs) and approved patterns into delivery-ready Low Level Designs (LLDs).
• Ensure designs align with architecture standards, data governance requirements, security controls, and platform guardrails.
• Drive solutions that are fit for purpose, operable, maintainable, and aligned to business outcomes, balancing value, risk, and reusability.
• Act as the first-line design assurance function, escalating only material variances and strategic decisions to Architecture.
• Own the quality and operability of delivery designs across both incumbent and emerging data platforms.
• Operate across data trains, hub teams, mid-tier demand, and small change deliveries, driving consistency in design approaches and engineering practices.
• Identify and promote reuse opportunities, reducing duplication and preventing unnecessary divergence across teams.
• Collaborate with Senior Data Engineers to shape solutions that are optimal for Severn Trent’s data platforms and operating model.
• Provide expert technical leadership, coaching engineers on best-practice patterns for data ingestion, transformation, storage, and serving.

Staff Data Engineer

• Design, develop, and maintain scalable data infrastructure to support our BI/MI workloads.
• Manage and optimize data pipelines and ETL/ELT processes.
• Ensure high availability, performance, and reliability of our data platforms and services.
• Conduct code reviews, mentoring others, and enforce best practices in data engineering.
• Diagnose and resolve data quality issues, ensuring accuracy, efficiency, and security.
• Maintain the confidentiality, integrity and availability of LMAX information assets

Data Operations Engineer

• Support in analysing technical requirements to determine project scope and deliverables
• Participate in the collection, research and analysis of source data
• Research and evaluate engineering source data and specifications
• Develop or maintain technical publication elements for all levels of maintenance, retrofit and repair
• Coordinate the preparation of illustrative materials
• Coordinate engineering requirements, schedule and status with all stakeholders
• Conduct quality and in-process reviews including the validation of technical publications

Support Engineering Data Specialist 2

• Design, develop, and maintain software applications using modern programming languages and frameworks.
• Work closely with cross-functional teams, including product managers, UX/UI designers, and QA engineers.
• Analyze complex problems and identify the most effective solutions.
• Write unit tests and perform debugging to ensure software quality.
• Create and maintain technical documentation, including system designs, API documentation, and user guides.
• Provide support and troubleshooting assistance to internal teams and end-users.

Software Engineer – Data & AI

• Develop robust scalable data pipelines and optimise data storage solutions on GCP.
• Implement ETL processes and CI/CD pipelines to ensure clean, structured data ready for use.
• Work with data scientists to integrate synthetic models into production environments and provide the guardrails and advice as they develop.
• Provide technical support, troubleshoot issues, and research new technologies to enhance capabilities.
• Document pipelines and the platform including architectures and user guides, helping to enforce data management standards.
• Engage in DataOps practices and improve data delivery performance.
• Partner with data scientists on model productionisation. You will establish clear data contracts and shared standards that enable effective collaboration.
• Work within an agile framework and participate in agile ceremonies.

Data Engineer – Audience Measurement

• Help our sales and presales solutions team to win new contracts by engaging with Insurance technology owners, data and AI lead to map business value delivery into data framework solutions.
• Define transformative data architecture engineering solutions, from project scope to backlog with our techs, PMs and POs.
• Lead customer project delivery as a data architecture, AI enablement or data engineering lead on Insurance tech solution transformations.
• Co-own the internal and customer-facing data framework and capabilities catalogue (and value delivery tracking) as part of our AI roadmap team, and Insurance solutions portfolio.
• Lead data and AI metadata project discoveries with enterprise clients in UK Insurance and Banking.
• Define data architecture and engineering patterns.
• Design proportionate data and AI governance.
• Assess data asset viability and RAG patterns.
• Collaborate with business and tech SMEs and POs.
• Support engineering teams to build data capabilities.
• Design production readiness and governance.
• Assist in change management and adoption activities.

Data Architect – Insurance

• Driving knowledge and understanding on the benefits and challenges of all aspects of data across PwC and our clients
• Defining the data strategy across the entire Data Landscape and Beyond
• Working closely with client EAs, CDOs and CIOs to educate and help them understand the different elements of data and how they fit into their architecture and business
• Resolving key design decisions focusing on data architecture, data migration and solutions
• Proactively assisting in the management of a portfolio of clients, reporting to Partner & Director Level
• Developing project strategies to solve complex technical challenges for our clients
• Managing and delivering large projects by developing the project team, assessing engagement risks throughout, driving conclusions, and reviewing / challenging the output produced by the team
• Being actively involved in business development activities to identify and research opportunities on new/existing clients
• Shaping and deliver projects to meet and exceed the expectations of our clients and our own quality criteria

SAP Data Architect

• Analyse source and target data structures to understand differences, dependencies and risks
• Define and document data mapping, transformation and reconciliation rules
• Support the Business Architect in performing detailed data analysis to inform migration design
• Identify data quality issues and support the definition and execution of data cleansing and remediation plans
• Contribute to the definition of the overall data migration approach, including sequencing, dependency management and cutover considerations
• Produce clear migration specifications, validation rules and test data to support delivery and testing
• Support data migration testing activities, including reconciliation, issue investigation and resolution
• Assist in specifying data reporting and data quality requirements for migration and post‑migration states
• Provide input into operational data ownership, controls and post‑migration monitoring arrangements
• Work within programme governance structures, supporting mobilisation and ongoing delivery

Data Migration Lead – Data Transformation

• Develop and maintain robust and efficient data solutions and products including data transformation, data modelling, and reporting on both on-premises and cloud environments
• Build modern data lake/lakehouse architectures that support scalable, flexible data processing
• Enhance platform integration by leveraging domain events to enable more efficient and real-time data processing
• Champion the adoption of generative AI features such as Amazon Q and Copilot to deliver intuitive analytics experiences
• Build sophisticated solutions to deliver actionable insights, with a strong focus on performance, scalability, and data accessibility
• Enhance data engineering processes through automation, implementing CI/CD pipelines, and optimizing ETL/ELT flows to improve efficiency and maintainability
• Collaborate with cross-functional teams to translate business requirements into technical solutions, documenting them as GAPs and aligning them with Architects
• Facilitate data discovery and enhance data management processes using platforms like Open Metadata
• Ensure KPIs and documentation remain accurate and up to date
• Support data quality and compliance standards across the organization
• Initiate and experiment with new ideas and approaches that support the A&I department's strategy

• Design and deliver product data products on Databricks — owning ingestion, transformation, and serving layers across the medallion architecture (bronze/silver/gold) to produce certified datasets consumed across product, analytics, and the wider business
• Lead the hard problems in the domain — event schema governance across multiple products, identity resolution and sessionisation, high-volume event pipelines, and modelling the path from product usage to engagement and learner outcomes
• Define and evolve engineering standards — dbt patterns, event ingestion patterns, data contracts, testing, observability — and contribute to cross-cutting standards across the wider data function
• Own data quality and contracts for the data products you ship — implementing quality checks, maintaining contracts as the interface between producers and consumers, and ensuring issues are caught early and remediated cleanly
• Raise the technical bar around you — through code review, design input, pairing, and the kind of senior IC presence that lifts the engineers and analysts you work with
• Translate operational complexity — multiple product event sources, schema drift, ongoing integration of acquired products — into clean, durable engineering execution the business can rely on

Principal Data Engineer – Product Data

• Provide dedicated data engineering capability within the Data Analytics & Intelligence team
• Develop and optimise use of Microsoft Fabric
• Design and implement scalable data pipelines and reusable data models
• Improve how data is collected, stored, and managed
• Support the evolution of SQL-based database
• Design and implement data ingestion pipelines for new requirements
• Strengthen data foundations to enable BI and analytics teams to deliver insights

• Build and maintain data pipelines that power analytics, ML workloads, and product-facing applications
• Evolve our data platform alongside cloud platform engineers
• Design and implement scalable data infrastructure
• Develop data services and APIs that expose trusted data to product applications
• Own data quality and observability
• Partner with AI engineers, data scientists, analysts, and product teams to understand their data needs
• Uphold strong data privacy, security, and compliance practices

Data Engineer jobs in United Kingdom

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Enterprise Data Architect

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Data Platform Lead

Finance Data Architect

Data Architect – 24 month FTC

Technical Lead – Azure Databricks Data Platform

Staff Data Engineer

Data Operations Engineer

Support Engineering Data Specialist 2

Software Engineer – Data & AI

Data Engineer – Audience Measurement

Data Architect – Insurance

SAP Data Architect

Data Migration Lead – Data Transformation

Senior Data Engineer

Principal Data Engineer – Product Data

Data Engineer

Senior Data Engineer – 6 Month Contract