Note: The job is a remote job and is open to candidates in USA. NimbleFig is a data company that operates platforms transforming public information into clean, structured, real-time data. The Data Platform Engineer will build and operate large-scale ingestion systems, maintain data freshness and correctness, and develop scalable storage, indexing, and observability capabilities.
Responsibilities
- Design, build, and operate ingestion pipelines across tens of thousands of changing sources
- Keep data fresh, deduplicated, and correct as volume and source count grow
- Design storage and indexing that stays fast to query at scale
- Build the observability to know, quickly, when a source breaks or drifts
- Own reliability and the unglamorous correctness work that keeps the data trustworthy
- Work across the stack when it matters, from fetchers to schemas to query paths
Skills
- Strong backend engineering, fluent in Python and SQL
- Experience with large-scale data pipelines, distributed systems, or high-volume ETL
- A real bias for correctness, and the instinct to measure before trusting
- Comfortable owning a system end to end, from fetch to stored record
- Experience with search or vector indexes at scale
- Worked with web-scale crawling, feeds, or document parsing
- A history of hunting down the gnarly, intermittent data-quality bug
Benefits
- Remote across the US, or in person in San Francisco
- Real ownership: you will ship work that customers depend on
- A small, senior team with high standards and little process
Company Overview