Top Data Engineer Jobs in Manchester

The role involves assessing and improving AI/data platforms, ensuring scalability and reliability, and integrating multi-source data, with hands-on delivery.

Develop and maintain data pipelines and ETL processes using cloud-native technologies; support cloud and on-premise data integration and contribute to CI/CD and Infrastructure as Code activities.

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

The Senior Microsoft Data Engineer will design and build business intelligence solutions on Azure, utilizing SQL Server, Data Warehousing, and BI practices to meet client needs.

The Data Engineer will develop data infrastructure, build data pipelines, implement workflows, and collaborate with teams to enhance data analytics capabilities.

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 will design and deploy production data pipelines, connect structured and unstructured data on AWS and collaborate with various teams to solve client problems.

The Data Engineer will design and maintain data infrastructure, develop data warehousing solutions, automate ELT pipelines, and ensure data governance while collaborating with stakeholders.

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

As a Data Engineer at UBDS, you will build data pipelines and solutions, collaborate in teams, and contribute to data-driven decision-making.

The AWS Data Platform Engineer will build and maintain data pipelines, improve data infrastructure, collaborate with teams, and ensure data reliability.

The Data Architect/Data Engineer will design scalable data architectures, build and optimize data pipelines, ensure data governance, and support advanced analytics and personalization, particularly using Adobe Experience Platform.

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.

Develop and maintain data ingestion and processing pipelines, collaborate with teams to build reliable data infrastructure, and support scalable solutions for decision-making tools.

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.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

The Senior Data Engineer will build cloud-native data pipelines and systems to protect clients from fraud, collaborate with teams, and maintain high engineering standards.

The Senior Software Engineer will build and enhance data pipelines, design backend services, maintain systems, and promote best practices across teams, emphasizing collaboration and adaptability.

As a Data Engineer at Starling, you will build cloud-native data warehouses and ML platforms, improving tooling within AWS and GCP.

Design, build, and optimize scalable data platforms across AWS and Azure. Enable data integration and support advanced analytics through cloud-based solutions and DevOps practices.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

As a Senior Data Engineer, you will design and develop large-scale data processing solutions and lead technical components in agile teams.

The Senior Data Platform Engineer will lead the development of scalable Snowflake services, automation, CI/CD pipeline design, and security controls to optimize data-driven healthcare projects.

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

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.