Data Engineer - Funds Management
- Build and maintain ETL workflows and automated data pipelines drawing on multiple data sources.
- Monitor data quality and integrity, troubleshoot system failures, and improve processes as business needs evolve.
- Work with investment data and modern cloud technologies, including Azure, Snowflake, SQL, and Python and/or R.
Our client is a diversified multi-asset fund manager offering products and strategies across Global and Australian equities. They are seeking a Data Engineer to join the analytics and insights team team, gaining exposure to investment data, APIs and modern cloud practices.
Key deliverables in the role:
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Extract, transform, and load (ETL) datasets from multiple sources
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Monitor and maintain datasets, ensuring quality and integrity through robust QA processes.
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Streamline automated data pipelines, build Docker images and distribute to Virtual Machines.
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Oversee system processes, troubleshoot issues, and resolve failures promptly.
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Redesign and implement processes in line with evolving business needs.
Skills & Experience:
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3-5 years' experience in a Data Engineering / Analyst role, with competency in SQL and data warehousing / MS SQL, Azure and Snowflake.
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Strong programming background (Python and/or R).
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Any exposure to Finance or Regulatory Reporting teams is highly regarded
If this sound like you, please apply through the link provided. Successful candidates will be shortlisted and contacted.
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