Senior Data Engineer
Posted Updated 6
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Summary
Senior Data Engineer building a next-generation lakehouse data platform using Databricks and AWS cloud-native services. The role involves developing scalable pipelines with PySpark and SQL, and utilizing tools like DBT and Airflow for a global investment firm.
We are partnering with a leading global investment firm undergoing a major data and cloud transformation. They are hiring experienced Data Engineers to build out their next-generation data platform.
This is a rare opportunity to work on a modern lakehouse architecture with Databricks at the core, fully integrated with AWS cloud-native services. This is a high-impact platform build, not a business-as-usual (BAU) maintenance role.
What You’ll Do
- Build scalable pipelines: Develop and maintain robust data pipelines using Databricks, PySpark, and SQL.
- Design AWS platforms: Architect and optimise enterprise data platforms on AWS cloud-native services.
- Power analytics: Work on enterprise-level data systems that drive critical investment and analytics use cases.
- Collaborate with stakeholders: Work closely with business teams to deliver real, data-driven impact.
What We’re Looking For
- Databricks Expertise: Strong hands-on experience with Databricks is a must-have.
- Modern Cloud Stack: A solid background in AWS combined with modern data tools (e.g., DBT, Airflow).
- Pipeline Engineering: Proven experience building scalable, production-grade data platforms and pipelines.
Why Join This Team?
- Executive Support: Benefit from strong leadership backing a firm-wide, long-term data strategy.
- Scale & Complexity: Gain exposure to large-scale, complex data environments within the financial sector.