Top Data Engineer Jobs in London

Design, develop, and optimize high-performance data pipelines and workflows on Databricks and AWS. Support L2/L3 production pipeline troubleshooting, implement monitoring and CI/CD deployment, and ensure data quality, security, and compliance. Collaborate with architects and analysts to build data models and performance-tuned transformations.

Lead technical delivery of cloud-native data and analytics products. Design and implement secure, scalable solutions, champion CI/CD and IaC, embed governance, mentor engineers, and collaborate with stakeholders to drive analytics platform strategy and operational excellence.

Client-facing role designing and delivering modern data platforms, architectures, and pipelines. Lead data strategy, governance, and engineering to enable analytics, ML/AI and GenAI use cases. Provide architectural leadership across programmes, support business development, thought leadership, and mentor junior staff while implementing cloud-native data solutions and governance frameworks.

Senior data quality engineer to design and execute data validation across ingestion, transformation, warehouse, BI, APIs and lineage. Maintain and extend dbt-based test harness, build automated checks using SQL/Python, integrate tests into CI/CD, perform reconciliation and regression testing across legacy and Snowflake platforms, and provide stakeholder reporting, defect triage, and knowledge transfer.

The Senior Data Platform Engineer will architect and build a scalable data platform, enabling teams to manage data with self-serve capabilities using modern tools. Responsibilities include developing microservices, leading technical initiatives, and promoting data governance and observability, collaborating with diverse stakeholders, and mentoring team members.

The Senior Data Engineer will enhance backend systems for a social media app by managing databases, optimizing recommendation algorithms, and ensuring accurate recommendations.

Lead technical pre-sales engagements for Databricks, demoing Spark and data/AI solutions, building architectures, authoring reference materials, and collaborating with account teams to design and deliver customised proofs-of-concept and workshops.

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

As a Senior Data Platform Engineer, you will design and operate a scalable data platform, support analytics, mentor junior engineers, and drive technical excellence.

As a Lead Data Engineer, you will design and develop software for data processing, lead a team, ensure quality, and manage technical proposals.

The Senior Data Engineer will design and implement data pipelines for fraud prevention, collaborate with teams, and ensure high quality code while participating in agile methodologies.

Lead pre-sales technical engagements for a data management/DSPM platform: perform technical discovery, architect solutions, run demos and POCs, enable partners, support RFPs, and liaise with product, marketing, and customer success to drive enterprise sales and adoption.

Define and build quality frameworks for human data programs, partner with clients and engineering to design evaluation, recruitment and annotation strategies, implement automated checks and dashboards, investigate data integrity, and upskill teams to deliver high-quality human data at scale.

Lead design and implementation of scalable generative AI services and reusable components using Python. Drive architectural decisions, deploy containerized applications on Kubernetes (EKS), ensure scalability/observability and CI/CD, mentor engineers, and collaborate with product and research teams to productionize LLM capabilities.

Lead and mentor a Data Engineering team to design, build, and optimize scalable Microsoft-based data platforms (Fabric, Databricks, Synapse, Azure). Develop PySpark/Spark SQL pipelines, orchestrate with ADF/Synapse/Fabric Pipelines, manage Azure DevOps and CI/CD, scope tasks, review code, and drive Agile delivery while acting as technical SME and stakeholder partner.

Design, build, and own end-to-end data pipelines on BigQuery and dbt; orchestrate workflows with Dagster; enable analytics and AI use cases; build marketing attribution and reverse-ETL; enforce data quality, observability, and platform standards.

Lead design and evolution of scalable real-time and batch ETL pipelines and data platform. Own performance, reliability, and data quality; drive architecture and tooling choices; collaborate with product and backend teams; mentor engineers and shape target architecture to support trader-facing analytics and low-latency data needs.

As a Data Engineer, you'll build and optimize data platforms, create data pipelines, and implement ML infrastructure to support business insights and data service needs.

Design, build, and maintain scalable data infrastructure and pipelines to support BI/MI workloads. Manage ETL/ELT processes, optimize performance and availability, resolve data quality issues, enforce security and governance, conduct code reviews, mentor engineers, and collaborate with product, data science, platform, and business teams.

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.

Design, build, and maintain scalable data pipelines and reusable platform components on Azure (Databricks, ADF, ADLS). Drive standardisation, CI/CD, data quality, observability, and performance optimisation while supporting Data Scientists and product teams with tooling, templates, and technical guidance.

Lead data architecture and strategy across OLTP, OLAP, and AI systems. Drive AI-first foundations (LLM orchestration, RAG, real-time inference), ensure DataOps/CI-CD, mentor technical leads, run architectural reviews, partner with product and engineering leadership, and optimise platform security, observability and costs.

The Software Engineer will manage data collection for model training, operate cloud infrastructure, and collaborate on data management strategy to enhance Speechify's AI capabilities.

The Senior Data Engineer will deliver complex data engineering for insights and analytics, collaborating with multiple stakeholders and managing team outputs.

The Senior Data Engineer will oversee data infrastructure, collaborate with product engineers, implement data governance, and drive cultural change regarding data usage within the organization.