Top Data Engineer Jobs in Bristol

Build and operate distributed ingestion and processing pipelines, ensure reliability and performance, define data contracts, add observability and testing, improve platform reliability and CI/CD, and participate in design/code reviews and incident retrospectives.

Design, build, maintain and evolve cloud-based data platform and ELT pipelines. Collaborate with stakeholders, implement data models and replication, ensure data quality, governance, documentation, and introduce new tooling.

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

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

The Data Engineer designs and maintains data products and pipelines for analytics, working collaboratively with the Information Management Pod to ensure data integrity and performance.

The Data Engineer will build and maintain data infrastructure, optimize performance pipelines, and ensure efficient data ingestion and querying for analysis within a high-performance AI media platform.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Build and maintain BigQuery data models and Python data pipelines using Dataform and Airflow. Implement data quality checks, observability, and CI/CD; containerize workloads with Docker; support Data Science productionization and contribute to Looker reporting.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

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

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

The Data Engineer will design and support data warehouses, create analytics dashboards, perform data quality analysis, and identify process improvements. Responsibilities include collaborating with stakeholders to develop insights and ensure data governance.

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.

Build and improve data pipelines that ingest, normalize, and distribute European power market data. Enhance APIs, monitoring, alerting, and performance; collaborate with data scientists and market experts to expand coverage and develop new product features.

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.

Design, build and maintain scalable data pipelines and Airflow orchestration; deliver Databricks-based data engineering solutions; collaborate via GitHub, support data science workflows, and promote observable, maintainable production delivery.

Design, build, and maintain scalable data pipelines and models (ingestion, modelling, orchestration). Ensure data quality via testing and monitoring, participate in code reviews, shape data architecture, and enable analytics/BI across the organisation.

Design, build, and maintain scalable ETL/ELT pipelines and modern lakehouse architectures. Optimize data solutions using Databricks, Spark, and AWS. Produce high-quality Python code, data models, and monitoring to ensure data accuracy, reliability, and performance. Collaborate with product teams, troubleshoot complex data issues, and improve infrastructure scalability.

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 Software Engineer, you'll manage data collection and infrastructure for AI model training, collaborating with scientists and stakeholders to enhance data processing workflows.

Design and maintain reliable data solutions, lead a squad of engineers, develop scalable data pipelines, and ensure adherence to data standards.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

The Senior Site Reliability Engineer will design and maintain a reliable data platform, develop data pipelines, automate processes, and ensure system observability while collaborating across teams.

Lead end-to-end development and productionisation of time-series forecasting ML solutions: design, train, deploy models, build cloud-native data pipelines, collaborate with stakeholders, and monitor model performance to optimise clinic scheduling and staffing.