Top Data Engineer Jobs in Bristol

The Data Engineer will build and scale data pipelines, ensure data quality, implement dbt best practices, and empower cross-functional teams with self-service data access.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Build, optimise and stabilise AWS-based data pipelines (S3, Glue, Redshift, Lake Formation). Resolve technical debt, support the Architect on target-state design, collaborate with client engineering teams to transfer knowledge, and deliver production-ready platforms in regulated, high-volume gaming environments.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Build and maintain production data pipelines and features in Python; own project lifecycle from design to reliable production; set technical direction for the Insights platform; improve engineering standards (testing, observability, data quality); apply AI across products and pipelines; help establish semantic/AI-ready data layers.

Design, build, test and document secure batch and real-time data pipelines, perform logical/physical database design and data modelling, expand platform capabilities, analyse and resolve data processing issues, and ensure alignment with data architecture for downstream consumers.

Build, test, and document secure batch and real-time data pipelines for a government client; design logical and physical databases; extend platform capabilities; ensure data models align with architecture; perform data analysis and root-cause investigations to improve processing and availability for downstream consumers.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Develop stored procedures or notebooks to build 230 additional data items into DCoE tables/views. Create an extensible, config-driven process to add fields with minimal re-engineering. Produce self-documenting, well-commented code and collaborate with the DCoE team on delivery; DCoE handles business analysis, design sign-offs, data modeling, and testing.

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

Design, build and optimise ETL/ELT pipelines and data foundations across enterprise systems. Profile, cleanse, map and reconcile data, implement quality frameworks, develop scalable data models on cloud platforms, and work with stakeholders to establish repeatable data architecture, governance and reporting for transformation programmes.

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.

As a Senior Data Engineer, you will design and develop large-scale data processing software, manage technical components, and mentor team members, while ensuring code quality and operational readiness.

Lead QA and test strategy for an AWS-native big data platform. Define automated test frameworks, validate large-scale data pipelines (PySpark/EMR), integrate tests into GitLab CI/CD, manage risk and reporting, mentor QA teams, and ensure data integrity across cloud data lake workflows.

Design, build and optimise scalable cloud-native data platforms and pipelines using Microsoft Fabric, Azure Databricks, Synapse and ADF. Implement ETL/ELT with PySpark and SQL, ensure data governance, performance, reliability, and collaborate with data scientists and engineers to deliver production solutions.

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.

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

Lead insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

Lead the development of backend services for government clients, focusing on high availability and scalability, while collaborating in agile teams and maintaining deployment pipelines.

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.