Technology & Change Recruitment for the Investment Management Community
We are looking for a dedicated Data Engineer to join the Finance Analytics Technology team at a leading Investment Manager. In this role, you’ll play a key part in building, maintaining, and optimising a modern data ecosystem. This permanent opportunity involves working with leading technologies, including Snowflake, Python, and Azure, to deliver high-quality data solutions that support business-critical decision-making.
With a hybrid working model and three days a week in the office, this role provides the chance to collaborate closely with cross-functional teams in a dynamic and supportive environment.
Key Responsibilities:
1. Design, build, and optimise scalable data pipelines using ETL and ELT methodologies.
2. Utilise Snowflake for efficient data storage, processing, and analytics.
3. Automate data processes and integrate data from multiple sources using Python and SQL.
4. Leverage Azure cloud-native technologies to enhance data infrastructure, ensuring scalability, performance, and security.
5. Participate fully in the agile development lifecycle, including sprint planning, design reviews, and delivering data tasks within two-week cycles.
6. Ensure compliance with existing standards while contributing to the refinement of best practices in cloud data engineering.
7. Expertise in building data pipelines and architectures with Snowflake and Python.
8. Familiarity with Azure and other cloud-native technologies.
9. Strong understanding of finance-related data domains and their application in data engineering.
10. Knowledge of reporting tools such as Power BI.
11. Familiarity with SAP FI or platforms like SAP BW, SAP Analysis, and Business Objects or Informatica or similar ETL tooling.
This is an exciting opportunity to contribute to meaningful data-driven initiatives, working with a forward-thinking team on innovative projects. If this sounds like your next step, we’d love to hear from you!
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