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# Data Engineer

- **Company:** Databricks, Inc.
- **Location:** Manchester, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Systems Engineering, Automation of Tests, Microsoft Azure, Databases, Continuous Integration, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Retrieval, Data Warehousing, DevOps, File Transfer Protocol (FTP) SSL Extension, Python (Programming Language), Windows PowerShell, Scala (Programming Language), Selenium, SQL Databases, YAML, File Transfer Protocol (FTP), Data Ingestion, System Availability, Large Language Models, Apache Spark, Deep Learning, Kubernetes, Playwright, Bicep, Terraform, Data Pipelines, Docker, Databricks
- **Published:** August 12, 2026
- **Apply:** https://www.careerjet.co.uk/job/gb9d8f7f714352f7e155c98d9b685eac2e/eaa

## About the Role

Databricks is the big one. Alongside that, we're looking for strong Python, SQL/Spark and ETL/ELT experience, good knowledge of databases and data warehousing, including dimensional/Kimball principles, plus an understanding of platform, DevOps and systems engineering.
They also value genuine technical curiosity. If you keep up with new technology, experiment with AI/deep learning or have side projects outside your day job, they'll want to hear about them.
A STEM background is beneficial, but not essential.
Nice to have

 * Databricks Asset Bundles, Lakeflow Jobs/Pipelines, Unity Catalog, Volumes and/or Lakebase
 * Agentic or AI-enabled engineering workflows, LLM integrations or AI coding tools
 * Playwright/Selenium
 * Docker/Kubernetes
 * Terraform/Bicep
 * Agile development environments
 * Scala, PowerShell and YAML

## Description

We're working with a truly disruptive FinTech that is continuing to invest heavily in its data and technology capability.
With a growing Data Science function and around 3-5TB of new data being processed each week, they're looking for a Senior Data Engineer to help build and evolve the platform behind it.
This isn't necessarily a traditional Data Engineering profile. They're open to people from Data Engineering, Platform, DevOps or Systems Engineering backgrounds, but strong data foundations and hands-on Databricks experience are key.
The role
You'll work within a cross-functional team, helping continue the move towards a Databricks-native environment and building reliable, scalable data and platform capabilities.
You'll be working across:

 * Databricks, Python, SQL and Spark
 * High-volume data ingestion and transformation
 * Production ETL/ELT pipelines
 * APIs, SFTP/FTPS and automated data retrieval
 * CI/CD, automated testing and deployment
 * Platform reliability, monitoring and troubleshooting
 * Azure infrastructure, security and governance
 * Data Science, ML and increasingly agentic workflows

The focus is production engineering rather than building AI models, creating the foundations that allow Data Science and automated workflows to operate effectively.


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