AngelList is looking for a Head of Data Engineering to own the fidelity, accessibility, and modeling of data across the company, ensuring data is embedded at the core of every workflow to enable everything from internal reconciliation to investor-facing insights at scale.
Requirements
- 8+ years of experience in data engineering, analytics engineering, or data platform roles, with at least 3 years leading teams.
- Deep expertise in data modeling, pipeline orchestration, and quality frameworks in a complex domain like venture.
- Experience working closely with backend engineering; comfortable reviewing code, schemas, and logging patterns.
- Familiarity with financial systems, accounting data, or regulated environments is a plus.
Responsibilities
- Architect and maintain high-fidelity pipelines for internal product data and third-party integrations (e.g., regulatory data, banking systems).
- Define and manage canonical data models and metrics used across reporting, operations, and product workflows.
- Lead data quality efforts: validation, observability, lineage, and SLAs – building trust from ingestion to dashboard.
- Partner with engineering to influence schema design and logging at the source.
- Build and grow a team of high-agency data engineers and analysts focused on accuracy, reliability, and usability.
- Support product teams with experimentation and real-time decision infrastructure.
- Deliver self-service, well-documented data interfaces for internal teams and stakeholders.
Other
- You think like a product owner: you measure success by what data unlocks, not what it looks like.
- Strong collaboration skills – can bridge technical, operational, and business domains.
- Track record of building from scratch and operating in high-ambiguity environments.
- High integrity and craftsmanship. You bring precision to naming conventions, documentation, and model definitions.
- Engineers and product teams can collaborate in the office at least twice per week (Tuesdays and choice between Wednesday or Thursday).
