Data Engineering Lead
Location: Nottingham (Hybrid - 1 day per week onsite)
Salary: Up to £90,000 + benefits
Type: Permanent
Overview:
A national leader within their relative field is looking for a hands‑on Data Engineering Lead to guide, mentor, and shape a high‑performing data engineering function within a modern cloud‑native environment. This is an opportunity to lead by example - balancing strategic direction with technical delivery - while working with an advanced Azure and Databricks ecosystem.
You'll play a key role in building scalable, reliable, and high‑value data solutions that support analytics, reporting, and data‑driven decision‑making across the organisation.
Key Responsibilities:
Lead and mentor a team of data engineers, driving best practices and technical excellence.
Remain hands-on in solution design, development, and optimisation using Databricks and Azure data services.
Oversee the build and maintenance of data pipelines, ingestion frameworks, and transformation workflows.
Collaborate with architecture, analytics, and product teams to deliver robust, scalable data solutions.
Implement and enforce data governance, quality frameworks, and performance standards.
Drive continuous improvement in data engineering processes, automation, and cloud optimisation.
Contribute to the overall data strategy and roadmap, ensuring alignment with business objectives.
Tech Stack & Skills Required:
Strong hands‑on experience with Databricks (Spark, Delta Lake, notebooks).
Deep knowledge of Azure data services such as:
Strong background in Python and/or Scala.
Solid understanding of CI/CD practices for data engineering.Leadership & Delivery
Proven experience leading or mentoring data engineering teams.
Ability to balance strategic direction with practical, hands‑on delivery.
Strong stakeholder engagement and communication skills.
Experience shaping engineering standards, frameworks, and reusable patterns.
What's on Offer
Salary up to £90,000
Hybrid working (1 day per week in Nottingham)
Modern tech environment with autonomy and influence
Opportunity to shape and scale a data engineering practice
Discretionary bonus
And more