[Remote] Data Platform Engineer

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