Senior Data Engineer
Summary
Build scalable data pipelines and design AWS platforms with Databricks, PySpark, SQL, and modern tools for a global investment firm's next-gen data platform.
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.
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.