Associate Director - Data Engineering

About our Client

Our client is a leading financial services organisation with a strong presence in the credit and lending ecosystem. The organisation is focused on building scalable, technology-led financial solutions.

Roles & Responsibilities

• Team Leadership: Manage and lead a high-performing team of data engineers, coordinating cross-functional dependencies and fostering a culture of continuous learning and technical excellence.
• Strategic Execution: Drive and execute the technical roadmap for key data infrastructure, pipelines, and products, balancing short-term delivery with long-term strategic goals.
• Technical Excellence: Drive operational efficiency across teams by enforcing engineering standards and SDLC best practices. Own the overall performance, reliability, observability, and accuracy of data pipelines. Continuously optimize highly scalable, fault-tolerant data pipelines.
• Mentorship & Collaboration: Mentor senior engineers and act as the first point of contact for external stakeholders. Identify and resolve technical bottlenecks and resource constraints. Help to recruit and onboard data engineering talents to scale the team effectively.
• Troubleshooting & Incident Response: Proactively identify, diagnose, and resolve critical data pipeline and platform issues, minimizing downtime and ensuring system stability.

Ideal Candidate

• 10+ years of proven experience in data engineering, with a strong track record of managing complex technical programs.
• Deep understanding of scalable data systems with strong system design and architecture review skills
• Deep, hands-on expertise in Apache Spark, PySpark, and the Databricks ecosystem. Must have advanced knowledge of Delta Lake, Open Table Formats, Unity Catalog, and Databricks Asset Bundles (DAB).

On Offer

An opportunity to take ownership of a strategic Data Engineering mandate within a growing financial services organisation. The role offers significant leadership scope, technical ownership and the opportunity to build and scale modern data platforms.