Lead Data Content Curation Engineer

Required

• A bachelor's degree
• 10+ years in data engineering, database development or financial data platform engineering, including 5+ years working with financial datasets in investment management, financial services or financial data providers.
• Expert SQL, strong relational data modeling and practical experience building analytical views and performant data access patterns in PostgreSQL or comparable databases.
• Strong Python and production pipeline engineering skills, including testing, version control, CI/CD and operational monitoring.
• Strong understanding of relational and modern lakehouse architectures, SQL-based access and open table formats such as Apache Iceberg; deep expertise in every named platform is not required.
• Experience interpreting messy third-party datasets, resolving identifiers and relationships, managing historical changes and validating data at scale.
• Strong knowledge of financial reference and entity data, company fundamentals, financial statements, estimates and historical revisions, including point-in-time correctness and avoidance of look-ahead bias.
• Demonstrated domain expertise in at least one asset class or investment strategy, such as equities, futures, options, fixed income, credit, macro or statistical arbitrage, with an understanding of the underlying financial datasets, instruments, identifiers and research workflows.
• Hands-on experience using AI/LLM-powered development tools to accelerate data engineering, with the ability to apply AI-assisted capabilities to repetitive curation and automation tasks.
• Ability to work directly with research users, clarify requirements and rapidly deliver documented, reusable data products.
• We’d love if you had:
• Experience with S&P Capital IQ, FactSet, Bloomberg, LSEG or similar vendor content and licensing-aware data delivery.