2 months ago
Base Salary
$130k - $500k/yr
Responsibilities
- Organize and establish clear ownership for Snowflake data across projects and teams.
- Design role-based access controls and automate access provisioning and revocation.
- Implement row access policies and PII masking across sensitive datasets.
- Migrate vendor and internal data sources into governed, properly owned systems.
- Own Fivetran connector health and cost, Airflow/Astronomer pipeline reliability and on-call, and Hex governance.
- Monitor and right-size Snowflake warehouse spending.
- Build CDC, streaming ingestion, and other internal data platform tooling.
- Set data platform standards for other engineers to build against.
Requirements
- Hands-on experience administering Snowflake roles, grants, warehouses, and cost/performance tuning.
- Experience designing data access and governance models using RBAC, row-level security, and PII controls at scale.
- Experience owning vendor tooling such as Fivetran and Airflow/Astronomer end to end, including on-call responsibilities.
- Track record migrating or re-architecting live production data systems without disrupting dependent teams.
- Strong SQL and Python skills with sufficient infrastructure fluency to make independent technical decisions.
- Production experience owning CDC or streaming pipelines, including delivery semantics, partitioning, and safe system cutovers.
- Experience with technologies such as Debezium, Kafka, or Snowpipe Streaming is relevant.
Benefits
- Bi-annual performance bonus structure and equity grant vested over four years.
- Relocation and housing assistance may be available.
- Monthly meal, laundry, and personal wellness stipends.
- Free Equinox membership.
- Health, dental, and vision insurance.
- In-person work five days per week in the San Francisco, New York City, or London office.
Tech Stack
Categories
Data Engineering
About Mercor
Mercor builds an expert-powered platform that trains, evaluates, and deploys AI systems for AI labs and enterprises. It operates APEX to assess model performance on economically valuable tasks, and provides services such as custom AI agents and teams of vetted domain experts who encode organizational knowledge into AI. Founded in 2023 and headquartered in San Francisco, it is privately held and works with frontier AI labs and enterprise clients requiring strict data isolation.