Top Data Engineer Jobs in Edinburgh

The Cyber Security Data Operations Engineer will develop and manage data analytics applications, design solutions, and ensure effective documentation and user support for cyber security data processes.

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 design, development and deployment of scalable GCP data pipelines; migrate legacy platforms to GCP; build DBT transformations; orchestrate workflows with Cloud Composer/Airflow; write Python for data processing and automation; implement Terraform IaC; ensure data quality and governance; collaborate with stakeholders and provide technical leadership and mentoring.

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 will manage the end-to-end lifecycle of data pipelines, architect data solutions, liaise with clients, and ensure performance monitoring. Responsibilities include defining specifications for ETL processes, deploying Azure Data Factory pipelines, and collaborating with engineering teams on data integrity and reliability.

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.

Lead Data Engineers will build data platforms, create data lakes and warehouses, and transform data into integrated models while leading teams and advising clients.

The Senior Data Engineer will lead teams in building data platforms and pipelines for clients, focusing on data integration and analytics solutions using various technologies.

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 Software Engineer will develop data pipelines, manage cloud infrastructure, and collaborate with AI scientists to enhance data acquisition for model training.

Lead and shape the Security Data & AI Lab's data engineering capability: define strategy and roadmap, own scalable cloud-native data pipelines and platforms, embed secure-by-design and engineering best practices (CI/CD, testing, observability), enable production-grade foundations for AI/ML, mentor engineers, and partner across Security, Cloud, Architecture and Product teams.

Lead development of ClickHouse's Python connector and SDKs, build integrations with orchestration and transformation tools, drive AI/LLM integration strategy for production data workflows, engage with open-source community, and collaborate across product and platform teams to deliver enterprise-grade data integrations.

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.

Lead the development of backend services for government clients, focusing on high availability and scalability, while collaborating in agile teams and maintaining deployment pipelines.

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.

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.

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.

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.