Data Engineer

Title: Data EngineerClient: Private Equity firmLogistics: 4 days per week onsite in SF or NYCCompensation: $160-190k base plus annual bonus - TC $275-325kCompany OverviewJoin a tech-focused private equity firm that has raised over $50 billion in capital and invests exclusively in technology companies. The team operates like a high-performance startup, combining institutional scale with a lean, high-caliber environment where every role has direct impact on investment decisions.The RoleJoin a small, embedded team building the data foundation that powers our client's investment platform. You'll work across the full data lifecycle, from ingestion and transformation to supporting the AI and ML systems that drive deal diligence, portfolio monitoring, and decision support.What You'll DoBuild and maintain scalable ELT/ETL pipelines across our modern data stackOwn data modeling and transformation workflows in dbt and SnowflakeIntegrate data from external APIs, financial data providers, and internal sources via AWSCollaborate closely with the AI engineering team to prepare datasets for embedding pipelines, vector stores, and retrieval systemsSupport data quality, observability, and documentation across the platformRequirements2+ years of experience as a data engineerStartup experience strongly preferred (Series A through C)Proficiency in SQL and PythonHands-on experience with Snowflake and modern data stack tools such as dbt, Airflow, or equivalentsFamiliarity with AWS data services, warehousing patterns, and API integrationsExposure to datasets that feed AI/ML systems including embeddings, vector stores, and retrieval pipelines