Top Data Engineer Jobs in Bristol

The role involves developing data pipelines, managing metadata and data quality in Azure, ensuring compliance with data governance standards, and collaborating with data teams.

Build and maintain scalable data pipelines and platform components to serve analytics, ML, and product teams. Design data services/APIs, ensure data quality, observability, security and compliance, and evolve cloud-native infrastructure using IaC and Kubernetes. Partner with cross-functional teams, produce documentation, and ship reliable, tested data solutions.

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.

Design, build, and maintain scalable data pipelines and platform services to support analytics, ML, and product teams. Implement infrastructure-as-code (Terraform) and Kubernetes-based deployments, develop data services/APIs, and ensure data quality, observability, security, and compliance. Partner with cross-functional teams, document systems, and continuously improve performance and reliability.

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.

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.

Design and deliver scalable Customer Data Platform solutions (Oracle Unity), build and operate data pipelines and Customer 360 models, integrate CDP with data lake/CRM/marketing systems, lead architecture and data modelling workshops, ensure data quality, governance, security, and support CDP operations, and partner with Oracle implementation teams.

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 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 Senior Software Engineer II will design and implement generative AI services, drive architectural standards, mentor engineers, and collaborate across teams to enhance data solutions.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

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.

As a Senior Data Engineer, you'll design and develop data processing solutions, collaborate with architects, mentor team members, and ensure operational readiness in agile teams.

Customer-embedded Principal Data Scientist who leads account-aligned delivery: translate business needs into technical approaches, build and ship production-grade solutions, influence senior stakeholders, prepare transitions to FDE crews, and operate with speed and entrepreneurial ownership to drive sustained business outcomes.

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.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

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.

Translate business needs into technical solutions by collecting, cleaning, and analysing data from multiple sources; build and maintain dashboards and reports; use SQL and Python to automate data processes; ensure data quality; present findings to stakeholders and collaborate across teams to drive process improvements.

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