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# Senior Data Engineer

- **Company:** RSK Group
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £50,000.0 - £80,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Automation of Tests, Code Review, Continuous Integration, Information Engineering, Python (Programming Language), Performance Tuning, Software Engineering, SQL Databases, Workflow Management Systems, Azure Data Factory, Sql Optimization, Snowflake, Git, Information Technology, Software Version Control, Data Pipelines
- **Published:** September 16, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5885195895

## About the Role

A relevant degree (e.g. computer science, engineering, mathematics) or equivalent practical experience.

Substantial data engineering experience, including time in a senior or lead role with clear technical ownership of a platform.

Expert SQL, including performance tuning and the design of well-structured, maintainable data models.

Strong Python for data engineering - pipeline development, automation, enrichment logic and reusable tooling.

Deep experience with a cloud data warehouse and its performance, cost and security models; Snowflake is highly desirable.

Hands-on experience with modern data stack ingestion and orchestration tools such as Fivetran and Azure Data Factory.

Strong, demonstrable experience with DBT for tested, documented and version-controlled transformations.

Software engineering discipline: Git, CI/CD, automated testing, code review and documentation as habits rather than aspirations.

## Description

Take technical ownership of the ingestion and platform layer -designing, building and running the pipelines that bring data from a wide and varied estate of source systems into our Snowflake warehouse using Fivetran and Azure Data Factory.

Lead the shift from manual, file-based feeds to direct, automated, granular connections to source systems, and standardise the feeds that cannot be replaced.

Design a repeatable onboarding pattern so that connecting a newly acquired business is a known, time-bound piece of work rather than a bespoke project each time.

Own reliability, performance and cost of the platform - orchestration, monitoring, alerting and incident response - and remove the recurring manual intervention that quietly consumes team capacity.

Write advanced SQL and Python, favouring reusable frameworks and well-tested patterns over one-off scripts.

Set and enforce engineering standards across the team: version control, CI, automated testing, code review and documentation.

Work hand in hand with analytics engineers so that data lands in a shape the DBT transformation layer can depend on, and with analysts and business stakeholders so that solutions fit the actual need.


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