Senior Data Engineer writing production code and maintaining data pipelines for commercial banking insights. Collaborating with other teams to deliver powerful data solutions.
Responsibilities
Write production code daily, most likely in Python, building and maintaining the data pipelines that power our Insights products.
Own the full lifecycle of your projects: understanding the data domain, designing pragmatic solutions, shipping them, and keeping them running reliably.
Drive technical quality through strong engineering practices — testing, observability, data quality checks, and clean, maintainable code.
Collaborate with product, data science, and engineering stakeholders to shape what we build and how we build it.
Identify opportunities to apply AI within our products and workflows where it delivers genuine value.
Contribute to the growth of the team by sharing knowledge and championing good engineering practices.
Requirements
Strong software engineering fundamentals: you write well-tested, production-ready code and care about maintainability, observability, and operational excellence.
Solid experience with modern data engineering tools and patterns — some combination of SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and DBT.
Proficiency in a strongly typed language, ideally Python or C#.
Comfort with modern deployment practices: CI/CD, containerisation (Docker), and cloud-based infrastructure.
A product mindset — you want to understand the business domain and use that understanding to influence what you build, not just how you build it.
The ability to communicate clearly with both technical and non-technical colleagues.
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