Gravitas is partnering with a growing financial services organisation seeking a Lead Data Engineer to become the most senior hands‑on technical contributor within their data engineering function.
This role is ideal for an engineer who thrives on solving complex technical challenges while elevating the standards, capability, and confidence of the wider team. You’ll lead on architecture, build high‑quality Databricks workloads, and act as a mentor and role model for engineers at all levels.
If you’re passionate about technical excellence, enjoy influencing best practice, and want to help shape a modern Azure‑based lakehouse, this is an excellent opportunity to step into a high‑impact role.
What You’ll Be Doing
* Act as the technical authority within the team, leading architecture decisions and ensuring high engineering standards.
* Design, build, and optimise scalable data pipelines on Databricks, integrating sources such as SQL Server.
* Develop and maintain Delta tables, workflows, and jobs within the Databricks lakehouse.
* Support the build and productionisation of ML feature pipelines alongside analytics and data science colleagues.
* Ensure all pipelines are well‑tested, monitored, observable, and thoroughly documented.
* Mentor junior and mid‑level engineers through code reviews, pairing sessions, and structured knowledge sharing.
* Contribute to engineering best practices, documentation, tooling, and platform maturity.
* Support the ongoing development and optimisation of the organisation’s Azure data infrastructure.
* Work with the Head of Data Engineering and CDAO to shape and deliver the technical roadmap.
What You Bring
Technical Skills
* Strong hands‑on experience as a data engineer, with a history of leading complex technical delivery.
* Advanced proficiency in Databricks - Delta Lake, PySpark, workflows, orchestration.
* Strong Python and SQL capabilities.
* Experience working with Azure cloud services.
* Demonstrable experience coaching, mentoring, or upskilling fellow engineers.
Nice to Have
* Experience with SQL Server and hybrid on‑prem/cloud architectures.
* Exposure to ML feature engineering or feature store development.
* Experience working in financial services or other regulated environments.
* Understanding of data governance practices, frameworks, and tooling.
What’s on Offer
* Discretionary annual bonus
* 25–30 days holiday (based on service) + birthday day off
* Pension scheme with up to 5% matched contributions
* Manchester-based role with office-based probation, then 3 days hybrid working thereafter
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