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TypeSafe is an AI lab building production-grade AI systems that combine LLM reasoning with code reliability. The company recently launched Jev, their first System One Model, and is backed by a16z with $870M in Series A funding.
As a Data Platform Engineer, you will own the data infrastructure and internal tooling that powers engineering, analytics, and business operations across the company. You'll work on the full data stack—from ingestion and storage through transformations and access controls—ensuring data is reliable, performant, and accessible to all teams.
Key responsibilities:
- Design, build, and maintain data pipelines, infrastructure, and internal tools
- Support data transformations, analytical models, and BI workflows
- Manage data access controls and permissioning
- Improve system reliability, performance, and data quality
- Partner with cross-functional teams to understand and support their data needs
The team is small, flat, and close-knit, working fully in-person from the San Francisco office near Embarcadero. The culture emphasizes craftsmanship, emotional honesty, and collaboration. Benefits include 100% covered health insurance, daily lunch and dinner, visa sponsorships, and 401K plans.
REQUIREMENTS (Must-Have):
- Experience in data engineering, infrastructure, or backend systems
- Proficiency with Kafka, ClickHouse, and data orchestrators (Dagster or Airflow)
- Strong SQL skills and experience with data transformations and permissioning
- Understanding of how data infrastructure supports BI and analytics
- Demonstrated ownership, collaboration, and adaptability
- Genuine excitement about the mission and working on a small team
REQUIREMENTS (Nice-to-Have):
- Experience building and operating large-scale, production data systems
- Background in building internal tools and supporting analytics teams
- Experience on teams with strong engineering standards
- Familiarity with AI and its practical applications