Data Platform Engineer

NimbleFig; California; Hybrid; USD 170,000 - 230,000; Full time

Benefits offered by this job

Competitive pay

Remote across the US

Ownership of shipped work

Small, senior team with high standards

Job summary

NimbleFig is hiring for a backend-focused data ingestion role in California. You will own the systems that ingest millions of documents from thousands of sources, ensuring fast, correct, and queryable data as volume grows.

The role emphasizes ownership from fetchers to stored records and requires strong Python/SQL skills and experience with large-scale data pipelines. Offer includes remote across the US or in-person in San Francisco, with compensation ranging from $170K to $230K depending on

Qualifications

• 5+ years backend engineering experience
• Proficient in Python and SQL
• Experience with large-scale data pipelines or distributed systems
• Bias for correctness and measurement before trust
• Comfort owning a system end to end from fetch to stored record
• Experience with search or vector indexes at scale

Responsibilities

• Design, build, and operate ingestion pipelines across tens of thousands of 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 observability to quickly detect source issues or drift
• Own reliability and correctness work to keep data trustworthy
• Work across the stack from fetchers to schemas to query paths

Skills

Backend engineering

Python

SQL

Distributed systems

Data quality

Observability

Tools

ETL

Search/Vector indexes

Job description

You will own the systems that pull in millions of documents from tens of thousands of sources and turn them into clean, structured, queryable data. This is the core of what we do: ingestion that stays fast, correct, and current as volume grows. It is unglamorous, high-leverage work, and it is the foundation every one of our platforms is built on.

About NimbleFig

NimbleFig is a data company. We acquire and operate data platforms that turn the world's public information into clean, structured, real-time data for people and machines, across news, places, government, and markets. Most of it is written for human eyes, scattered across millions of sources, and out of date the moment it ships. Our job is to make each part of that record complete, current, and ready to query. We are a small, senior team, and the work is measured by one thing: whether the data is right, current, and easy to use.

What you'll do

• 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

What we look for

• 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

Compensation

Depending on experience, the expected pay range in California is $170K–$230K.

What we offer

• Competitive pay, in the range listed above
• 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

How we hire

We read every application. If there is a fit, expect a short intro call, a practical exercise rooted in the kind of work you would actually do, and a few conversations with the people you would work with. A link to something you have built beats a resume.