Top Data Jobs in London

Design and govern enterprise-scale data architectures and pipelines across operational and analytical domains. Ensure data products align to standards and strategy, support cloud migration to Azure and Snowflake, provide architecture assurance, chair Data Design Authority, embed governance and MDM, and enable data readiness for AI/ML initiatives while liaising with business and delivery teams.

Consulting role focused on Workday Financials data migration, transformation, validation, and optimisation. Lead tenant-to-tenant migrations, design conversion templates, develop ETL and reconciliation tools, validate loaded financial data, and collaborate with clients and project teams throughout implementation.

The Senior Manager, Data Strategy leads the execution of the data strategy for the UK Government, translating strategic vision into actionable data solutions while ensuring ethical data use and driving collaboration across teams.

The Data Engineer will build and maintain data infrastructure, optimize performance pipelines, and ensure efficient data ingestion and querying for analysis within a high-performance AI media platform.

The Platform Data Analyst will enhance visibility and performance optimization of Runware's media AI platform through analytics, monitoring, and reporting. Responsibilities include tracking performance, building dashboards, and collaborating with engineering and DevOps teams to improve observability and reliability.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

Support building overseas data product systems (AI agent, BI, self-service analysis). Coordinate with dev/design to implement and optimize product solutions, analyze global game data, and communicate with studios and customers to understand needs and deliver targeted data-driven solutions.

Lead UK account strategy and growth for data center customers, build and sustain strategic client relationships, own pipeline and forecasts, drive capture teams and must-win pursuits, support cross-functional solution proposals, and travel domestically (~35%).

Lead design and delivery of scalable analytics, BI, forecasting, and AI-driven solutions for RevOps Sales Intelligence. Partner cross-functionally to improve data quality, governance, automation, and self-service analytics using cloud data platforms and modern ML/Generative AI techniques. Manage roadmap, stakeholder communication, and operationalize AI/analytics at enterprise scale.

Build, deploy, and iterate predictive models and real-time scoring pipelines using behavioral and clickstream data to improve lead quality and campaign optimization. Collaborate with marketing, media buying, and analytics teams to translate business needs into hypotheses, perform exploratory analysis, monitor model performance, and communicate statistically rigorous insights to non-technical stakeholders.

This role involves designing and optimizing a blockchain data platform, focusing on ETL pipeline development, data quality, and system scalability. The engineer will collaborate with cross-functional teams to enhance data access and enable product engineering efforts.

As a Data Scientist, you'll empower the company with data insights, develop metrics and experiments, and collaborate with various teams to drive product decisions.

The Senior Data Engineer will design and maintain scalable data pipelines, ensure data quality, and develop backend services to support WalletConnect's payments infrastructure and analytics.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

The Data Standards Lead will develop and govern data standards for licensing, ensure data interoperability, and guide teams in applying these standards.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.

Lead a team of engineers to develop data-intensive systems, drive technical direction, and improve engineering processes while maintaining hands-on involvement in code and architecture discussions.

Lead high-complexity analytics projects: partner with stakeholders, prepare and blend large datasets, apply intermediate statistics, build models and visualizations, deliver insights, and mentor junior analysts.

The Executive Partner manages a portfolio of clients, providing expert guidance in Data & Analytics, mentoring executives, and ensuring client value through various engagements. Responsible for retention and growth, the role emphasizes collaboration with internal teams and requires strong executive presence.

The Senior Product & Growth Data Scientist will analyze user behavior, run experiments, shape product strategy, and influence growth metrics to drive company success.

Design and implement core YTsaurus functionality in C++, build and evolve platform-level capabilities, improve APIs and UX for internal users, own production quality including incident response/on-call, and collaborate with stakeholders to prioritize and deliver scalable data platform features.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.