Top Data Jobs in London

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 Senior Data Consultant will deliver enterprise-level Data Analytics solutions, mentor team members, interact with clients, and foster innovation.

The Data Consultant role involves delivering enterprise applications in Business Intelligence and Data Analytics, focusing on client relationship management and data solution development.

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.

As a Principal Data Architect, you will design and implement modern data solutions, ensuring data quality and governance while managing architectural direction for engineering teams and guiding clients on data strategy and integration using Google Cloud technologies.

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.

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.

Design, build, test and maintain ETL/ELT pipelines and analytics warehouse (Snowflake/dbt). Implement data testing, governance, observability and self-service capabilities. Partner with analysts, data scientists and stakeholders, troubleshoot data issues, and mentor colleagues to improve data reliability and analytics processes.

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

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

The Data Engineer will design and architect data systems for real-time workloads, mentor junior engineers, and ensure data reliability and security.

Lead administration and roadmap for BI tools (Domo, Tableau); build advanced dashboards with custom code; automate ETL with Airflow and Jenkins; use SQL, Python, and Java; apply AI to speed development; train and mentor analysts and ensure high-quality, user-focused data visualizations.

Own and professionalize the commercial data function: define metric semantics and governance, lead a small data team, deliver executive-ready reporting and forecasting, and build a roadmap for applied AI and predictive analytics on a governed single source of truth.

The Data Solution Architect will lead the design and implementation of data solutions, advocate for data-centric practices, ensure data privacy, and collaborate across teams to improve data ecosystems.

Hands-on engineer roles to modernise and scale a cloud-native, low-latency global financial platform. Work on software, data, platform and SRE problems prioritizing performance, data quality, reliability, CI/CD automation, and AI-assisted development tooling. Collaborate across global teams to deliver production-grade systems on AWS/Azure.

Lead Workday HCM data conversion and implementation efforts: design, map, cleanse, transform and load client data using Workday tools, develop monitoring and reports, validate data, and support clients through project phases.

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.

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 day-to-day GDPR and privacy compliance: chair the GDPR Task Force, handle privacy queries, coordinate DPIAs and due diligence, maintain RoPA/DPIA registers and supplier records, review data processing agreements, provide guidance and training, and drive privacy actions across technical and commercial teams.

Lead end-to-end ML and GenAI projects across a two-sided marketplace: frame problems, prototype, deploy and monitor models (LLMs and classical ML), drive commercial impact, partner cross-functionally, and raise data science standards while mentoring juniors.

Lead and grow a Predictive Growth Optimisation team to own Flo's pLTV system, build Marketing Mix Modeling, and develop real-time algorithms and production ML systems that optimize user acquisition and marketing spend while partnering with Growth, Product, and Finance.

Manage and enforce data governance frameworks, standards, and lifecycle controls across enterprise data platforms. Coordinate between business and technical teams to ensure data quality, access controls, lineage, reusability, and compliance in a regulated environment.

Develop and deliver machine learning models (churn, propensity, CLV, recommendations) using large-scale behavioral and transactional data. Translate business problems into modeling approaches, partner with cross-functional stakeholders, communicate insights, and expand use of advanced methods (deep learning, sequence models) to drive player engagement and value.

Apply causal inference methods to measure incremental Customer Lifetime Value, design and analyze experiments and observational studies, quantify drivers of player value from large-scale data, and translate causal insights into actionable recommendations for stakeholders.