Data Engineer (Databricks)

TL;DR

Data Engineer (Databricks): Designing and delivering data pipelines and products to support reporting, analytics, and AI across the business with an accent on reliability and usability. Focus on building end-to-end data products using SQL, Python, and PySpark to integrate complex source systems.

Location: Hybrid (Cambridge, UK). In-office expectation: once every two weeks. Must be able to travel to the office safely in a day.

Salary: £50,000 - £60,000

Company

Redgate builds solutions that help data professionals securely manage the data and databases that their organizations depend on.

What you will do

• Own the reliability and usability of business data by designing and delivering robust data pipelines.
• Build end-to-end data products on Databricks using SQL, Python, and PySpark, from ingestion to curated models.
• Integrate multiple source systems with varying levels of quality and maturity.
• Balance data modelling, performance, and cost to build durable, scalable solutions.
• Define and improve data engineering standards for testing, observability, and cost efficiency to enable future AI use cases.

Requirements

• Proven experience as a Data Engineer.
• Practical experience working with Databricks.
• Strong SQL and data querying skills.
• Proficiency in Python and PySpark for building and maintaining data pipelines.
• Experience with source control solutions like GitHub and methodologies such as Git Flow.
• Must be based in or able to commute to the Cambridge office.

Culture & Benefits

• Flexible-hybrid work model blending remote and office work.
• Environment built on trust, accountability, and collaboration.
• Opportunity to work on a modern, evolving data stack and shape engineering standards.
• Work on high-impact products that deliver visible value across Finance, Commercial, and Operations.

Hiring process

• Human-led application review by Talent Partners.
• Initial conversation to align on expectations and get to know the candidate.
• Skills alignment interview involving technical assessments or competency-based questions.
• Values alignment interview to ensure cultural fit.