Fundable - Senior Data Engineer

Fundable is a startup data platform that helps investors and other teams discover and research companies. We bring together information on companies, investors, funding activity, and people to make that research easier.

We’re looking for a senior data engineer to own Fundable’s data platform from architecture through production, reliably turning high volumes of data from provider APIs, webhooks, files, and web scraping into trusted records for our products.

Today, our enrichment and extraction workflows largely run serially inside a container. You’ll lead the move to a platform that supports concurrent processing, event-driven intake, and orchestrated batch workflows.

• Experience building multi-source production data platforms from zero to one, from initial architecture and pipeline implementation through deployment and ongoing operation.

• Production experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or Temporal, including dependencies, retries, and failure recovery. Airflow experience is preferred.

• Hands-on production experience with dbt and GCP.

• Experience building event-driven systems with messaging or task queues, including asynchronous processing and failure recovery.

• Strong SQL and PostgreSQL skills, including data modeling, query optimization, and reliable incremental loading. Experience with data contracts, raw and curated storage, retention policies, and automated quality checks.

• Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.

• Hands-on web scraping experience with tools such as Scrapy, Playwright, Selenium, or Beautiful Soup, including concurrent scraping, rate limits, and failure handling.

• Experience working in startups or small engineering teams, with broad ownership and changing priorities.

• Entity resolution experience is especially valuable: matching company and people records across sources and reconciling duplicates into consistent entities.

• LLM-based structured extraction or company and people data enrichment.

• Familiarity with BigQuery and Dataform.