Top Data Jobs in London

Lead design and deliver scalable, secure Azure-based data architectures for insurance platforms (Lloyd's marketplace). Translate business objectives into end-to-end solutions, provide architecture leadership across data platforms and integrations, drive strategy and innovation, support underwriting/claims/policy processes, create roadmaps and data storytelling, and manage stakeholder expectations and governance throughout projects.

Lead design and delivery of a secure, scalable Microsoft-based data platform and centralized reporting for financial and operational metrics. Build centralized data model, manage ingestion/transformation/semantic layers, develop Power BI dashboards, ensure compliance, and engage senior stakeholders to translate needs into technical solutions while driving adoption.

Design, build, and maintain Power BI dashboards and automated workflows using Microsoft Power Platform and ServiceNow. Write and optimize SQL for Snowflake and other databases, perform data validation and lineage, support Workday/ServiceNow integrations, provide go-live support and troubleshooting, and uphold data management and governance practices across corporate and client-facing teams.

The Software Engineer will develop betting solutions, create mathematical models, automate operations, and collaborate closely with data scientists.

Develop advanced automation and visual data processing workflows using AI tools, focusing on computer vision and data streaming techniques while ensuring system reliability and scalability.

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.

Lead the development of data products by analyzing customer needs, improving data structures, and creating actionable insights through collaboration with cross-functional teams.

The role involves collaborating with researchers and traders to design datasets, developing data pipelines, and optimizing data extraction processes.

Embed in the Pitstop squad to build monitoring and analytics for launch readiness, handover speed/accuracy, retention, and cost-per-parcel. Investigate performance, quantify initiative impact, diagnose churn and LiveOps ticket drivers, maintain dbt models and pipelines, and deliver KPIs and dashboards to guide squad decisions.

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

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.

Provide EU-focused data privacy and digital regulatory legal counsel across business segments. Lead privacy program development, support HR, Marketing, M&A, and transactional work, manage incident response, regulatory engagement, DPIAs, cross-border data transfers, and advise on EU Data Act, GDPR, data governance, and product compliance.

As a Data Architect, you will define data architectures for client programs, driving data and AI transformations, and crafting secure and scalable data solutions across various technologies.

The Product Data Science Manager leads a team to deliver custom data insights, ensuring analytical excellence and client impact while collaborating with various stakeholders.

The Data Platform Engineer will scale and modernize the data lakehouse, build data products, write ETL processes, and support analytics across the business.

The Forward Deployed Data Solution Engineer works embedded within teams to ensure software quality, guide technical decisions, and design integration patterns, focusing on AI-enabled capabilities and data governance.

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 maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Support ledger migration and data lake cleanup by extracting, transforming, reconciling and validating large datasets. Develop and validate SQL queries, batch jobs and processing logic, perform regression testing, document mappings and validation rules, and collaborate with engineering, product and business teams to ensure production readiness and post-migration validation.

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.

As a Senior Data Scientist, you'll develop AI solutions with machine learning, mentor others, and ensure responsible AI practices while collaborating with clients to solve business challenges.

Lead a small senior data engineering team owning the end-to-end data platform: streaming, warehousing, modelling, pipelines, ML lift, and operational excellence. Drive delivery, coach engineers, review technical designs, enforce data contracts and quality, manage costs (FinOps), and partner with Product and leadership to set roadmaps and risk. Build and grow an emerging ML function.

Design, build, and maintain scalable batch and streaming data pipelines, internal tools, and APIs to support analytics, product features, and ML. Collaborate with product and engineering to improve data infrastructure, ensure reliability, testing, and observability in a cloud-native environment.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.