The Client:
Financial Services, Ethical, highly cerebral colleagues, collaborative environment and meritocratic. Amazing location in Manchester City Centre, hybrid working 3 days in, bespoke Bonus and solid benefits. Industry leaders utilising highly progressive Modelling & Analytics, Simulations and more.
This is a hybrid role, Manchester City Centre based 3 days per week and comes with a solid Bonus and some fantastic benefits. You’ll be surrounded by Analytics, Data Science and Engineering Colleagues in this meritocratic and highly collaborative team.
The Role:
You’ll be the most senior hands-on technical contributor within the team, you will aid in the design and delivery of complex engineering workloads, provide mentorship to the wider team, and help set and uphold engineering standards across our Databricks platform. The ideal candidate combines deep technical expertise with a natural inclination to bring others along with them.
🧑🏽 🏫Act as the technical authority within the data engineering team, leading on architecture decisions and code quality.
🧱Design, build, and maintain robust data pipelines on Databricks, integrating data from SQL Server and other upstream sources.
🐟Develop and optimise Delta tables, workflows, and jobs within the Databricks lakehouse.
🪈Support the development and productionisation of ML feature pipelines in collaboration with the analytics team.
🚿Ensure pipelines are well-tested, monitored, and documented.
🧘🏻Mentor and support junior and mid-level engineers through code reviews, pair programming, and knowledge sharing.
Requirements:
We’re looking for a seasoned Data Engineer with the following skills and experience:
* Strong hands-on experience as a data engineer, with a track record of leading complex technical delivery.
* Advanced proficiency in Databricks (Delta Lake, PySpark, workflows).
* Strong Python and SQL skills.
* Experience with Azure cloud services.
* Demonstrable ability to mentor and upskill less experienced engineers.
* Desirable: Experience with SQL Server and hybrid architectures.
* Desirable: Exposure to ML feature engineering or feature store development.
* Desirable: Experience in financial services or a regulated environment.
* Desirable: Familiarity with data governance practices and tooling.
The interview process will be two fold and online. We can commence interview w/c 7th April 2026. Feel free to reach out to Daniel Holdsworth at PeopleGenius for more information.
Keywords: Data Engineer, Senior Data Engineer, Lead Data Engineer, Azure, Data Bricks, DataBricks, Snowflake, Data Engineering, Python, SQL