AI Data Engineer, Data Platform

Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.

Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures, QED Investors, Google’s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.

We are looking for a Data Engineer to own and scale the data platform that powers analytics, reporting, and AI across Collective. You will design, build, and maintain the pipelines that move data from our product, financial, and third-party systems into our BigQuery warehouse; model that data into clean, well-documented, reliable tables; and set the engineering standards that keep the platform trustworthy as the company grows.

You will join the Data Engineering team within Engineering and work closely with product engineers, analysts, and business stakeholders across Operations, Finance, and Go-to-Market. This is a hands-on role for someone who cares about data quality, takes ownership of production systems end-to-end, and wants their work to be the foundation the rest of the company builds on.

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• Experience with streaming or event data (Pub/Sub, Kafka, or similar) and product analytics tooling (Amplitude or similar).

• Experience with Terraform and Google Cloud Platform infrastructure.

• Experience with observability platforms such as Datadog.

• Exposure to financial, accounting, tax, or payroll data and the correctness requirements that come with it.

• Experience building semantic layers or metric stores consumed by LLM-based tools, or supporting LLM evaluation programs.

• AI-assisted development experience (Claude Code or similar).