Top Data Jobs in London

Senior advisory role to define and scale CPG data foundations: shape multi-year roadmaps, prioritise platform capabilities, guide data acquisition/harmonisation and governance, engage executive stakeholders, and translate complex data/architecture decisions into commercial outcomes.

Lead the Salesforce ecosystem for customer engagement, owning Marketing Cloud, Data Cloud and personalization. Manage a small data automation team, ensure reliable data flows and hygiene, design integrations, enforce change controls and governance, enable personalization at scale, and support reporting and measurement for commercial and CRM activity.

Own and build end-to-end credit and fraud models for a B2B BNPL product: design, deploy, monitor, and improve supervised ML on tabular and time-series data, collaborate with product and risk, and develop pipelines and monitoring for portfolio performance.

As a Data Engineer, you will design, build, and maintain data pipelines and infrastructure to support data-driven decision-making in a collaborative environment.

Lead the development and architecture of new data services and products around clinical insights, focusing on data analysis and reporting.

The Senior Category Sourcing Manager leads sourcing initiatives, manages contracts across various categories, coaches a team, and implements strategies for cost savings and efficiency.

The Data Platform Architect will lead complex data engineering projects, act as a trusted advisor to customers, and guide their data platform strategy while documenting architectural designs.

This role involves designing and delivering enterprise-level data solutions using Azure tools to help businesses gain insights from their data repositories.

The role focuses on leading data platform strategy and architecture, guiding enterprise clients on modernizing their data ecosystems for AI, and enhancing the data platform capabilities within Simple Machines across Europe.

Lead the design and implementation of modern data platforms and pipelines, ensuring high performance and compliance while consulting directly with clients to drive effective data solutions.

Lead the Risk Platform Operations team to ensure accurate and timely delivery of portfolio risk analytics, mentor junior members, and enhance data quality controls.

As a Data Analyst/Consultant, you'll undergo extensive training on data visualization and integration using Tableau and Alteryx, working with renowned clients to build your skills and confidence as a consultant.

As a Data Engineer, you'll optimize the Data Lake and develop pipelines for data-driven decision-making, collaborating with Data Science for efficiency.

Provide specialist legal advice across EMEA on data privacy (GDPR), digital, AI and technology matters. Advise on vendor/cloud contracts, outsourcing, cybersecurity incidents, regulatory implementation, and support IT and business transformation projects while managing external counsel and aligning global practices with local rules.

Build and maintain reliable ingestion and transformation pipelines on Databricks or Snowflake, design Data Vault 2.0/Kimball models, ensure production reliability, support testing/monitoring/documentation, and help apply LLMs and AI-enabled solutions in regulated financial services environments.

Lead hands-on delivery of production data platforms on Databricks or Snowflake, build reliable ingestion pipelines and data models, mentor junior engineers, integrate LLM/AI where appropriate, ensure production reliability and compliance, and support pre-sales technical sizing and proposals.

The Data Scientist designs and deploys data models and automation solutions, collaborating with teams to meet business needs through data-driven insights.

The role involves building and implementing machine learning models, collaborating with cross-functional teams to solve complex problems in data science.

Develop and deliver machine learning models (churn, propensity, CLV, recommendations) using large-scale behavioral and transactional data. Translate business problems into modelling solutions, collaborate with engineering, product, and commercial teams, communicate insights to stakeholders, and explore advanced methods (deep learning, sequence models) to drive player engagement and value.

Lead a team of data analysts as the maritime SME for vessel and company datasets: ensure data accuracy, design and maintain ETL and ingestion pipelines, implement automation and validation using SQL and Python, integrate new data sources, create dashboards, manage KPIs/OKRs, and collaborate with Product, Engineering, Data, and Commercial teams to deliver high-quality maritime intelligence.

As a Senior Data Engineer, you will enhance data governance, improve data quality, and ensure compliance. You'll lead implementations, develop observability systems, and mentor teams to strengthen data reliability across the organization.

Lead delivery of advanced AI solutions, provide technical and architectural leadership, drive adoption of cloud-native AI engineering, and manage, coach, and develop a multidisciplinary data science team while ensuring responsible AI practices and strong stakeholder engagement.

Lead and grow a data science team to design, develop, evaluate, and deploy production-grade AI/ML solutions (LLMs, Generative AI, RAG, transformers). Own technical vision, MLOps/LLMOps, model governance, and cross-functional execution with Product and Engineering to deliver scalable business impact in financial markets.

Design, build, and maintain end-to-end ETL pipelines and a shared ETL framework. Write tested mapping and validation code, perform code reviews, mentor junior engineers, and collaborate with product, QA, and client teams to deliver accurate, production-ready data integrations to regulatory standards.

Productionize and support analytics and AI solutions by building reliable Python-based data workflows, deploying containerized/cloud services, modernizing legacy analytics, and collaborating with data science, engineering, and business teams. Provide EMEA support, create documentation and runbooks, and maintain Power BI dashboards and recurring analytical workflows.