Top Data Jobs in London

The Director of Colleague Data Science & Analytics will lead the global HR analytics function, driving innovative solutions to support decision-making and enhance the colleague experience.

The Data Solution Architect will design and implement cloud-based data and AI platforms, ensuring scalable data solutions and effective communication with clients.

The Data Engineer will implement cloud-native data platforms, engineer scalable pipelines, and optimize cloud resources using Python and SQL, while applying agile methodologies and cloud automation tools.

As a Senior Data Analyst, you will gather and document business requirements, manage stakeholders, analyze complex datasets, and create data models and dashboards.

The Senior Data Engineer will design and build data pipelines on GCP, ensuring high data quality and reliability for analytics and ML products. Responsibilities include mastering ETL processes, managing workflows with Airflow, and collaborating closely with ML engineers.

Build end-to-end testing, evaluation, and feedback systems for a global GenAI assistant. Design data pipelines, APIs, and dashboards; own features from design to production; ensure safety, compliance, and quality; provide technical leadership and mentor peers.

Contribute to the Data Engineering team by building data models, optimising the Data Warehouse, and improving data quality while applying best practices.

The Lead Data Enterprise Architect will guide technology direction, ensure compliance with architecture policies, oversee large-scale projects, and develop effective enterprise strategies and processes.

Seeking a Software Engineer for Regulatory Reporting to build backend systems ensuring compliance. Responsibilities include system design, data integration, and audit support.

As a Senior Data Engineer, you will manage complex data projects, lead small teams, and work with clients on data engineering solutions. Responsibilities include ETL development, data pipeline orchestration, and customer relationship management.

Lead project teams in delivering bespoke algorithms, mentor other data scientists, and shape client relationships in the defence and national security sector.

The Curriculum Manager will oversee the content development lifecycle, recruit instructors, design curriculum, assess course performance, and improve data science and engineering content.

Short-term consultant to maintain WaterAid's research and data monitoring functions: manage the KRSP, integrate and format databases into the Statistics Bank/Power BI, update JMP/GLAAS WASH datasets, produce monthly KRSP usage reports, convene research clinics, and support research design, procurement and quality assurance over a four-month assignment.

The Data Management Lead defines data strategy and architecture for telecom data, aligning it with AI and automation, while driving product innovation and implementing scalable solutions.

Design, build, maintain and evolve cloud-based data platform and ELT pipelines. Collaborate with stakeholders, implement data models and replication, ensure data quality, governance, documentation, and introduce new tooling.

Lead AI vision and multi-year roadmap for the Financing Platform; prioritize AI/GenAI use cases; drive discovery, experimentation, MVPs and scaling; ensure governance, testing, monitoring and Responsible AI; partner with engineering, data and product teams; enable stakeholder adoption and training; track KPIs/OKRs and report outcomes to leadership.

Serve as product-owner/business analyst for actuarial data and tools within the Global Data Office. Translate actuarial requirements into data engineering specs, lead Agile ceremonies, manage product backlog and roadmaps, align stakeholders, and ensure data governance, lineage, testing, and quality for actuarial reporting, reserving, and pricing use cases.

Lead delivery of Data & AI projects: design cloud-native data architectures, guide Databricks/Snowflake implementations, pair-program with data engineers, own client technical relationships, support pre-sales, mentor and line manage engineers, and embed modern data and AI practices.

Design, build, and maintain large-scale data pipelines and tooling for petabyte-scale logs, events, and model traces. Ingest, clean, transform, version, and monitor datasets; ship analytics and dashboards; support production, testing, and research workloads; troubleshoot pipeline issues and improve reliability.

Lead and productize the organisation's Snowflake-based data platform: define multi-year strategy, run the platform as a product, deliver curated data products and monetisation, own roadmap, governance, SLAs and vendor relationships, and build a high-performing data engineering team while partnering with Product, Security, and Cloud teams.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

As a Data Engineer, you will develop and maintain ETL pipelines, manage data infrastructure, and support data-related projects to drive business insights.

Lead data science initiatives to enhance player engagement and business outcomes through machine learning solutions, collaboration, and technical leadership.

Lead the development and delivery of data solutions for customer analytics. Manage a distributed team to ensure quality, secure, and scalable data products. Collaborate with product teams to align technical and business needs, establishing engineering guidelines and driving automation in data processes.

Lead analytics strategy and standards across product and business teams; build reusable measurement frameworks, apply causal inference and forecasting, pioneer AI-accelerated analytics, mentor data scientists, and translate results for executives.