Top Data Jobs in London

Lead the vision, strategy, and roadmap for ASOS’s enterprise data ecosystem and platform foundations. Define data product requirements, prioritize investments, collaborate with engineering and business stakeholders, and measure product outcomes. Establish data governance, quality, documentation, security, compliance, and ownership standards while enabling analytics, AI, and data-driven decision-making. Champion customer-focused discovery, iterative delivery, innovation, and organizational change across cross-functional Agile teams.

Senior client-facing consulting leader for Energy & Infrastructure who originates and leads AI- and data-enabled transformation engagements across UK/EMEA. Drives go-to-market, shapes solutions from discovery through delivery, leads multidisciplinary teams, owns P&L and pricing, and grows pipeline, revenue and margins while delivering measurable operational and commercial value for E&I clients.

Work in multidisciplinary teams to design, build and maintain data pipelines, models and analytics products using SQL, Python and modern data tools. Contribute to cloud-based data solutions (AWS/Azure), apply software engineering and data governance practices, create visualisations, and collaborate with stakeholders in Agile delivery to produce maintainable, production-ready data services.

Lead data architecture and resiliency for marketing data pipelines. Build scalable Airflow/dbt workflows, productionize CDP datasets, own MarTech integrations, bridge engineering and analytics, and mentor engineers to improve reliability and observability for high-volume streaming and batch systems.

Lead engineering of metadata, meta-modelling, and distributed systems; produce and review secure production Scala/Java code; drive adoption and governance of AI-assisted engineering across the SDLC; influence product design and operations; mentor technical teams; establish automation, validation standards, and reuse of proven patterns.

Lead the design and delivery of metadata, meta-modelling, and distributed systems. Develop and review secure, high-quality Scala/Java production code, adopt AI-assisted engineering practices, improve automation and operational stability, and apply cloud-native and SDLC best practices within an agile team supporting financial services applications.

Lead Data Engineer responsible for designing, building, and maintaining secure, scalable data collection, storage, access, and analytics solutions. Ensure data trustworthiness, create data models, implement backup/recovery/archiving, evaluate access control, and support data platform stability across business functions.

Lead design and delivery of metadata, meta-modelling, and distributed systems. Build secure, high-quality production code, drive adoption of AI-assisted engineering, improve SDLC automation and cloud-native delivery, set validation and governance standards, mentor engineers, and influence product and technical decisions.

Manage day-to-day privacy processes (RoPA, DPIA, DSRs), administer OneTrust and Jira, drive AI governance rollout, advise on data protection and consent, codify guidance and training, automate privacy operations, reassess high/medium-risk processing, and support data protection agreements with cross-functional stakeholders.

Develop, test, and support reliable, high-performance distributed Java applications for real-time streaming and concurrent workloads. Partner with stakeholders, present and review designs, improve reliability/observability/performance, and support production releases to meet SLAs within BGM Data & Analytics.

Designs and maintains enterprise-scale data pipelines, warehouses, and lakehouses using Python, Airflow, DBT, and Snowflake. Integrates structured and unstructured data, establishes data quality standards, and supports AI-ready infrastructure. Owns production operations, on-call incident response, observability, remediation, and documentation. Partners with ML, data science, product, and business teams; advises leadership on data strategy and infrastructure investments; and mentors junior engineers.

Leads a multidisciplinary engineering organization responsible for enterprise-scale data and AI infrastructure. Owns the data platform technical roadmap, cloud architecture, governance, security posture, FinOps, vendor relationships, and modernization programs. Provides architectural oversight, mentors engineers and architects, manages delivery planning, and aligns technical solutions with commercial and business goals. Requires extensive cloud data platform, data engineering, application development, governance, security, CI/CD, and stakeholder management experience.

Leads a multidisciplinary engineering organization responsible for enterprise data and AI infrastructure. Owns data platform architecture, technical roadmaps, governance, security, cloud cost optimization, vendor relationships, and modernization programs. Provides architectural guidance, mentors engineers, oversees migrations and integrations, and aligns product and engineering delivery with business goals. Requires strong expertise in cloud data platforms, data modeling, pipelines, application development, visualization, security, CI/CD, and AI/ML integration.

Generate actionable insights from complex customer, behavioral, lifecycle, and product data. Collaborate with product, commercial, CRM, content, and leadership teams to define analytical questions, test hypotheses, measure business impact, and support evidence-based decisions. Present clear data stories, challenge assumptions, promote data-driven decision-making, and automate recurring reporting and analysis.

Build and maintain reliable financial datasets for quantitative researchers and traders. Responsibilities include extracting, cleaning, aggregating, and onboarding data from diverse sources; developing robust extraction processes; investigating data quality issues; and improving onboarding tools. The role requires close collaboration with researchers, traders, engineers, management, and external data providers in a fast-paced quantitative investment environment.

Designs and delivers scalable data solutions on Azure, collaborates with engineers and architects, supports data and telemetry understanding, performs proof-of-concept work, and builds reliable, tested, maintainable systems using CI/CD. The role contributes to agile delivery, engineering standards, data modelling, performance and cost optimization, while developing expertise in modern data technologies.

Leads Babyzone’s data, impact measurement and evaluation strategy across its national hub network. Builds end-to-end data infrastructure, longitudinal outcome tracking, dashboards and trusted reporting systems; operationalises evaluation measures including the Parent Confidence Index and Good Level of Development analysis. Designs hands-on AI and automation workflows, ensures data protection and ethical governance, works with academic partners, supports policy influence, and builds organisational data capability through team leadership and frontline engagement.

Lead data strategy for key clients, design data-led audience solutions, champion Open Intelligence and Infosum, support AI tool development, and line-manage 1–2 Data Strategy Managers while collaborating with media planning and activation teams to drive client outcomes.

Analyze Spotify’s planning and execution data to develop hypotheses, statistical and machine learning models, data pipelines, dashboards, and actionable recommendations. The role translates complex operational and strategic information into narratives, reports, and decision frameworks for leaders. It also explores AI and automation for faster insight generation and collaborates with data scientists, engineers, product managers, and business partners across the company.

Develop and maintain Python applications, services, data processing solutions, and scalable ETL/ELT pipelines. Integrate structured and unstructured data from APIs, databases, files, and streaming systems while ensuring quality, performance, reliability, and security. Collaborate with engineering and architecture teams, contribute to data platform design, implement testing and monitoring, and support technical documentation and engineering standards.

Define, set up and ingest external clinical data streams (labs, ECG, imaging, EHR, wearables, genomics). Plan set-up activities, create trial-specific Data Transfer Agreements, translate medical concepts into data mappings, perform UAT, implement transfers into the CDR, monitor data quality and resolve provider conformance issues while ensuring regulatory and data protection compliance.

The Data Engineer will build and maintain data pipelines, ensuring quality and performance while collaborating with teams to support platform evolution and product delivery.

Leads mechanical design for mission-critical European data center projects, covering HVAC, cooling, chilled water, hydronic, plumbing, drainage, ventilation, and thermal systems. Coordinates multidisciplinary teams, consultants, contractors, vendors, authorities, and operations stakeholders. Reviews designs, calculations, specifications, equipment selections, and technical proposals for quality, compliance, constructability, reliability, efficiency, maintainability, and sustainability. Identifies risks and supports issue resolution through design, commissioning, handover, and operational readiness.

Partner with Product, Design, Engineering and Analytics Engineering to analyze customer behaviour, define KPIs, run funnel/cohort analyses, design and evaluate A/B tests, build dashboards, and surface actionable product insights to drive activation, engagement and retention.

Lead data engineering for the Flexibility team by establishing AWS-based data systems, scalable processing and warehousing, platform improvements, and architectural standards. Build foundational data capabilities, maintain critical applications, integrate with Databricks, improve operational reliability, and support global scalability. The role also involves mentoring backend engineers, defining requirements, documenting solutions, visualizing data, and collaborating with the broader data community.