Key Responsibilities

• Design, develop and maintain robust data pipelines for investment analytics using Python, SQL and Spark on AWS.
• Implement ETL processes to ingest, transform and load large volumes of market and alternative data into data lakes and warehouses.
• Collaborate with data scientists and portfolio managers to deliver high-quality, reproducible datasets for modeling and reporting.
• Optimize pipeline performance, monitor data quality, and troubleshoot issues in a production environment.
• Document architecture, code, and best practices to ensure maintainability and compliance.

Requirements

• 3+ years of experience in data engineering, preferably in finance or investment analytics.
• Experience with ETL frameworks, data modeling, and performance tuning.
• Excellent problem-solving skills and a collaborative mindset.
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