Top Data Engineer Jobs in Glasgow

Design, build, and maintain scalable Azure-based data pipelines and Microsoft Fabric artefacts; integrate data into ADLS/OneLake; perform ELT/ETL and advanced transforms using SQL, Python, and Spark; manage Power BI models; implement Purview governance; troubleshoot production issues; contribute to CI/CD, documentation, and mentor junior engineers while consulting directly with clients.

Entry-level data engineer to follow a structured 12-month development programme. Build internal reporting, reusable engineering frameworks, documentation, and tooling while learning SQL, Python, Databricks and cloud data services. Support senior engineers, join code reviews, shadow customer workshops, and progressively contribute to client projects.

Design, build and maintain cloud-native ETL/ELT pipelines and data lake solutions using dbt, Snowflake/Databricks and AWS services. Optimize SQL and data models for performance and cost, create dashboards, follow CI/CD and software engineering best practices, and collaborate with architects, engineers and clients to deliver production-ready enterprise data solutions.

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.

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.

Build and operate a new AI-focused data platform: design ingestion, transformation, semantic/ontology layers, storage, and DAG-based orchestration. Implement pipelines, select databases and orchestration tools, ensure performance, observability, and data quality, and collaborate with product and AI teams while remaining hands-on in coding and production operations.

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

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.

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 maintain scalable data pipelines and backend data-processing applications using Java and SQL. Optimize data models, query performance, and data platform reliability; implement automated testing, monitoring, and data quality controls; collaborate with stakeholders to translate requirements into scalable ETL/ELT and near-real-time solutions.

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

Build and maintain data ingestion, modelling and pipelines for client reporting. Validate data quality, develop Power BI dashboards and paginated reports, translate business needs into data solutions, and support stakeholders and team enablement during a major data platform transformation.

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.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

Client-facing Principal Data Engineer leading design and delivery of enterprise Databricks-based data platforms. Provide architecture leadership, mentor engineering teams, drive platform optimisation, define standards, support technical governance, and deliver across multiple consultancy engagements.

Support ledger migration and data lake cleanup by extracting, transforming, reconciling and validating large datasets. Develop and validate SQL queries, batch jobs and processing logic, perform regression testing, document mappings and validation rules, and collaborate with engineering, product and business teams to ensure production readiness and post-migration validation.

The Senior Data Engineer will design and deliver data solutions, mentor junior staff, and engage with clients to drive AI and data strategy while ensuring compliance and optimizing architectures.

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.

Lead design, development, and operation of real-time and batch data pipelines and cloud infrastructure. Improve reliability, observability, and data architecture; own features end-to-end and mentor engineering teams while coordinating cross-team stakeholders.

Design, build, and maintain scalable data pipelines and Airflow orchestration; deliver Databricks-based data engineering solutions; support data science workflows; collaborate via GitHub, code reviews, and shared engineering standards; ensure reliable, observable, and maintainable pipelines.

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.

Own and operate Databricks-based data platform production support, build and migrate ETL/ELT pipelines to Databricks across Azure/AWS, optimize compute and performance, enforce Delta Lake architecture and data security, implement observability and CI/CD, support multi-tenant onboarding and on-call incident response, and maintain runbooks and SLA metrics.

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, automated cloud data solutions and pipelines. Provide technical leadership to a small engineering squad, own complex backlog tasks, develop data frameworks and standards, and ensure code quality via reviews and pair programming using Databricks, Python, SQL and Spark.

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