relational databases · lakehouse
The Role
We are seeking a hands-on Lead Data Content Curation Engineer to transform complex financial and enterprise datasets into trusted, research-ready data products. Working closely with investment research teams, data engineers and platform specialists, you will translate raw vendor content into well-designed models, curated tables, views and reusable datasets across relational databases and modern lakehouse platforms. You will deliver usable data products quickly while progressively introducing AI-assisted curation and automation. This role focuses on data quality, usability and business meaning rather than database infrastructure administration.
What you’ll do
- Own end-to-end curation of external and internal datasets, from source evaluation and ingestion design through modeling, validation, publishing and ongoing evolution; prioritize rapid delivery of research-ready content.
- Interpret complex financial vendor data, including S&P Capital IQ and comparable fundamental, reference and market datasets: schemas, identifiers, relationships, update patterns and methodology changes.
- Design and implement research-ready relational and lakehouse data models, SQL transformations, curated tables, materialized datasets and performant views across PostgreSQL, SingleStore and Apache Iceberg-based platforms.
- Build shared, strategy-agnostic data products that support distinct investment workflows without duplicating core definitions, identifiers or historical logic.
- Enable seamless, location-independent discovery and access to trusted datasets through catalog, API and que