Data Engineer
Role details
Job location
Tech stack
Job description
We're looking for a passionate Data Engineer to join our innovative team in London or Newcastle and help shape the future of our Data Lakehouse platform! In this role, you'll collaborate closely with business and technology teams across Wealth Management Europe (WME), building and optimising the data pipelines that turn raw financial data into trusted, actionable insights using cutting-edge tools like Databricks, Azure Data Factory, and Delta Lake. This is a permanent, full-time role and requires working 4 days a week in our London or Newcastle office., * Architect & Optimize Data Pipelines: Design, build, and maintain scalable pipelines across our Bronze, Silver, and Gold medallion architecture - from raw source ingestion through to the analytics layer that powers our business.
- Own the Platform: Perform daily monitoring of pipeline health, proactively resolve issues end-to-end, and keep our data flowing reliably for the teams that depend on it.
- Innovate with Modern Tech: Leverage Azure, Databricks, and Data Factory to automate repetitive tasks, enhance performance, and future-proof our platform.
- Champion DevOps & DataOps: Lead by example with Gitflow branching, structured pull request reviews, and rigorous testing practices.
- Collaborate Across Teams: Partner with data analysts, architects, and business stakeholders to translate requirements into well-engineered technical solutions that drive strategic decisions.
- Innovate Continuously: Spot opportunities to improve pipeline performance, platform architecture, and engineering processes - and do something about them.
Requirements
- Proven experience in Data Engineering working within a Lakehouse environment (Databricks is preferable)
- Strong SQL/T-SQL skills and a knack for database design and modelling
- Experience and knowledge of Python and PySpark
- Proven experience building and optimising big data pipelines at scale with structured and semi-structured data
- Hands-on experience with Azure Data Factory, ADLS Gen2, and Azure SQL Database
- Solid Azure DevOps practices including Git, branching strategies, and agile delivery
- A thorough approach to testing - source system through to the presentation layer
Nice-to-Have
- Familiarity with Infrastructure-as-Code (e.g. Terraform)
- Experience with data governance, quality, and security processes.
- Familiarity with Azure DevOps Pipelines and CI/CD for data platform deployments
- A curious, problem-solving attitude and a passion for automating manual processes., Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Group Problem Solving, Quality Management, Requirements Analysis