Top Data Engineer Jobs in Glasgow

Seeking a Senior Data Engineer to design, build, and deploy AWS-based data pipelines for Tier 1 financial services, mentoring junior engineers while ensuring scalable and fault-tolerant solutions.

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.

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.

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.

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.

Lead and architect enterprise-scale cloud data solutions, mentor data engineers, design and build batch and streaming pipelines using Databricks and Microsoft Fabric, implement Lakehouse/Medallion patterns, ensure data governance/security, and drive CI/CD and IaC practices across projects.

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 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.

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 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.

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.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

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.

As a Senior Data Engineer at YLD, you'll design and build scalable, resilient data-driven solutions, collaborating with cross-functional teams to innovate and enhance productivity through AI tools.

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.

Design, develop, and unit test complex ETL/ELT and application integrations using Informatica (Real Time/Cloud/PowerCenter). Build SOAP/REST API components, write complex SQL, stored procedures and triggers, and collaborate with BI/IT teams to support the enterprise data integration hub and BI platform.

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.