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# Data Platform Engineer (Infrastructure & Data Engineering)

- **Company:** Insight
- **Location:** London, UK
- **Salary:** £50,864.0
- **Contract:** Permanent contract
- **Skills:** .NET Framework, Microsoft Azure, Continuous Integration, Information Engineering, Data Infrastructure, DevOps, Github, Python (Programming Language), Standard Sql, Software Deployment, Software Engineering, Systems Integration, Connectivity Problems, Delivery Pipeline, Infrastructure as Code (IaC), Terraform, Key Vault, Databricks
- **Published:** September 29, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5901872117

## About the Role

Strong hands-on experience with Microsoft Azure infrastructure (including Entra ID, Key Vault, networking, and storage).

 - Practical experience with Azure Databricks (including Unity Catalog and cluster/job management).
 - Proficiency in Terraform for Infrastructure as Code, preferably in multi-environment setups.
 - Proficient in Python; working knowledge of SQL; .NET experience is a plus.
 - Experience building and maintaining CI/CD pipelines (with Azure DevOps, GitHub Actions, or similar tools).
 - Understanding of data platform governance and cost management.
 - Comfortable working at the intersection of infrastructure and data engineering.

Key Technical Skills:

 1. CI/CD (Azure, DevOps, GitHub)
 2. Azure Databricks (Unity Catalog, cluster/job management)
 3. Microsoft Azure infrastructure

## Description

Design and maintain CI/CD pipelines: Develop and manage continuous integration and deployment workflows using DevOps tools (Azure DevOps, GitHub Actions) for both infrastructure and application deployments.

 - Infrastructure as Code (IaC): Write and maintain Terraform code to provision and manage Azure infrastructure and Azure Databricks resources (Unity Catalog, workspaces, networking, compute policies).
 - Application development and automation: Create and support platform tooling and automation scripts/applications in Python and/or .NET.
 - Shared libraries/modules: Develop and maintain reusable libraries and modules for use by data engineers and analysts.
 - Platform management automation: Design and implement automated processes for cost tracking, governance, resource provisioning, and monitoring of the platform.
 - Collaboration: Work closely with data engineers, analysts, and security/infrastructure teams to turn requirements into platform features and capabilities.
 - Troubleshooting: Diagnose and resolve issues related to infrastructure, pipelines, integrations (including networking, authentication, and connectivity problems).
 - Documentation & standards: Contribute to documentation and the development of best practices and standards for the platform.


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