Financial Data Analyst - Python

Overview

Financial Data Analyst role focused on developing and maintaining Python data pipelines for external financial datasets used on the firm’s research and trading platform.

What you'll do

• Develop and maintain Python-based data pipelines to ingest, transform, validate, and load external financial datasets.
• Onboard new datasets by mapping fields, defining schemas, running historical backfills, and deploying production data feeds.
• Own assigned datasets across their lifecycle by monitoring pipelines and resolving data delivery issues.
• Investigate and resolve data quality issues including missing data, duplicates, stale values, outliers, and identifier/calendar inconsistencies.
• Collaborate with external data vendors to resolve delivery issues and clarify data definitions and changes.
• Document datasets, transformation logic, and operational processes to support maintainability.

What you'll need

• 3+ years of experience in financial data, market data, data engineering, data operations, or a similar data-focused role.
• A bachelor’s or master’s degree in a quantitative discipline such as Mathematics, Physics, or Engineering.
• Advanced Python programming experience, including Pandas and NumPy.
• Experience with structured and semi-structured data such as CSV, JSON, XML, Parquet, APIs, or vendor data feeds.
• Experience with financial market data, reference data, pricing, fundamentals, corporate actions, ESG, or alternative datasets.
• Experience investigating data quality issues and reconciling datasets against independent sources.
• Familiarity with Git and modern development practices.

Details

• Collaborates with researchers, analysts, and engineering teams to deliver datasets meeting business requirements.