Top Data Jobs in London

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

Lead delivery and ongoing ownership of a modern, cloud-based data platform. Define migration and integration roadmaps, manage programme delivery, embed data governance, support data engineering teams, drive adoption, and optimise reporting, analytics and data quality to enable business decision-making.

Manage the full commercial lifecycle for enterprise and strategic customer accounts: renewals, pricing, contract amendments, upsell strategy, and expansion. Build bespoke commercial strategies using usage data and market context, forecast renewal pipeline, lead commercial QBRs, negotiate with senior stakeholders and procurement, and partner with Customer Success and solution consultants to quantify ROI and drive retained and expanded ARR.

Build and operate production data pipelines and streaming integrations ingesting market data and asset telemetry. Partner with trading and data science teams to deliver data for forecasting models. Work with stakeholders to build integrations and analytical views and improve the data platform powering GAIA across the business.

Lead and develop teams of data scientists, driving impactful projects through experimentation, causal inference, and applied machine learning while collaborating with various stakeholders.

Build and maintain ETL/data pipelines into the Data Lakehouse, develop Power BI dashboards, support AWS infrastructure (S3, Glue, Lambda, Step Functions, LakeFormation), ensure data quality using dbt, write complex SQL and Python for data processing, use Git for version control, document workflows, and collaborate with analysts and data scientists.

Owner of data stewardship and governance activities: implement data cataloguing, metadata standards, data quality metrics, business rules, remediation, and stakeholder engagement to ensure consistent, accurate data across teams.

Own the end-to-end data quality issue lifecycle, lead offshore analysts, liaise with UK stakeholders, partner with IT/Operations for fixes, drive preventive data quality improvements, and produce governance-ready reporting and dashboards.

Assist in implementing data governance frameworks and policies, ensuring data accuracy, creating data dictionaries, and contributing to data governance training and materials.

Lead and grow a Data Foundations engineering team owning ingestion, storage, identity resolution, and external data onboarding. Shape roadmap and technical direction, partner with tech leads on architecture, and drive team performance and delivery for a high-throughput streaming data platform.

The Technical Product Owner will manage data products, prioritize tasks based on business needs, and collaborate with cross-functional teams to deliver data solutions for mobile apps.

Lead development of behavioural features and detection algorithms from hypothesis to production using high-frequency GPS and inertial sensor data. Prototype, build scalable Python and SQL pipelines, evaluate ML and rule-based models, run experiments, and collaborate with engineering, product, and actuarial teams to integrate features into pricing and measure impact.

Lead Data Scientist defines technical direction and architects production-grade ML solutions, oversees end-to-end delivery and technical risk, scopes high-value proposals, manages client relationships, mentors data scientists, and drives adoption of best practices across multidisciplinary teams to deliver high-impact public-sector projects.

Collaborate with traders and researchers to design and build robust data systems for trading analysis in a fast-paced environment.

Lead strategy and execution of analytics and AI/ML products to measure and maximize player lifetime value. Drive cross-team alignment, prioritize roadmaps, define experimentation and modelling standards, and ensure scalable, production-grade ML capabilities are adopted and deliver measurable business impact.

Abstract and enter clinical data from healthcare records, apply clinical operations policies, troubleshoot VPN/MFA access, maintain confidentiality, and provide guidance to less-experienced team members while ensuring data quality and workflow adherence.

Lead global market intelligence for Iron Mountain Data Centers by analyzing macro trends, cloud architectures, and power constraints; build GIS-based site selection tools; embed market data into underwriting and financial models; deliver investment recommendations and standardized market frameworks to executive leadership.

Manage client relationships as a subject matter expert, collaborating with Account Executives to drive revenue, engage clients, and provide product insights for innovative solutions.

Senior data analyst/programmer using SAS or R to analyze commercial claims and EHR real-world data. Create longitudinal cohorts, derive baseline/outcome variables, assess data quality, apply epidemiologic study designs and statistical methods (regression, survival), review protocols/SAPs, and program TFLs. Familiarity with OMOP CDM and OHDSI tools is a plus; prior pharmaceutical experience preferred.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Design, develop, and deploy machine learning and LLM-based solutions for risk scoring, compliance prediction, churn analysis, and contractor analytics. Integrate models into production on AWS and Azure, use Microsoft Fabric for data pipelines and feature engineering, implement model monitoring and retraining, and collaborate cross-functionally within an Agile SDLC.

Client-facing Principal Data Engineer leading design and delivery of enterprise Databricks-based data platforms. Provide architecture leadership, mentor engineering teams, drive platform optimisation, define standards, support technical governance, and deliver across multiple consultancy engagements.

Lead design and implementation of data governance and MDM strategies, develop policies and metadata/lineage practices, enforce data quality, deploy governance tooling, engage stakeholders, ensure regulatory compliance, and mentor team members.

Design, build, and maintain scalable cloud-based data platform and ETL pipelines on Azure. Develop data models, ensure data quality, optimize performance, implement governance and security, and collaborate with stakeholders and data scientists to enable data-driven solutions.

Translate business needs into technical solutions by collecting, cleaning, and analysing data from multiple sources; build and maintain dashboards and reports; use SQL and Python to automate data processes; ensure data quality; present findings to stakeholders and collaborate across teams to drive process improvements.