Founding Data Infrastructure Engineer

Own the how, not just the what: apply strong product sense to set direction, shape standards, and elevate execution.

Build and maintain Jane's customer data infrastructure end-to-end: the systems, pipelines, and source integrations that carry product and marketing events from collection to warehouse. Today there are multiple independently configured sources with different conventions; you'll bring consistency and reliability.

Work directly with marketing, paid media, analytics, marketing operations, BI, and product as primary stakeholders, including on attribution questions, campaign tracking, conversion data, and the integrations that connect our marketing tools to the warehouse. The stakeholder surface is wide and cross-functional, and your ability to build trust across teams matters as much as your technical depth.

Drive tooling strategy for Jane's collection layer, including our CDP, event pipeline, and ingestion infrastructure. We currently run RudderStack and are evaluating the right long-term stack; you'll help determine what that looks like and build toward it while keeping the lights on.

Establish instrumentation standards within engineering, product, and marketing, defining how product and web events are structured, named, versioned, and validated, while ensuring clean handoffs, shared standards, and alignment on what good data looks like at Jane.

Take ownership of identity resolution and attribution at the collection layer. A prospect's journey crosses multiple channels, domains, and touchpoints (including marketing pages, landing pages on third-party platforms, and a separate signup application), and that journey needs to stitch together cleanly so that funnel data is trustworthy and Jane has a reliable picture of what's driving growth.

Navigate the realities of consent-gated instrumentation. Jane operates in healthcare, which means our tracking infrastructure interacts with PHI compliance requirements, consent management, tag management, and third-party marketing tools. You'll design instrumentation that works reliably within those constraints.

A University Degree in Computer Science or a related STEM field plus hands-on experience as a data engineer or similar, including time operating at a staff level or higher — depth and judgment matter more here than a specific number of years. You've built and maintained event collection, customer data infrastructure, or data pipeline systems in production. You've inherited and rationalized independently built pipelines, not just built from scratch.

You're comfortable leading and owning both the strategy as well as the execution: making the architectural calls, being the person other teams and leadership look to for direction on this domain, set standards that teams actually follow. You influence and drive strategy clearly across engineering, product, BI, marketing, and leadership.

Experience evaluating or implementing Customer Data Platforms including migrating or consolidating existing tooling. Greenfield-only experience is not sufficient for this role.

Experience with privacy-compliant tracking and consent management. You've worked with consent management platforms, understand how consent state affects data collection, and have designed instrumentation that holds up within those constraints, ideally including server-side tagging or tag management systems. Experience in healthcare or other regulated environments is a plus.

Strong opinions (loosely held) on schema design, event taxonomy, and data quality. You've seen what happens when instrumentation is an afterthought, and you care about getting it right.

Experience with identity resolution, attribution, or cross-domain tracking. You understand the complexities of stitching a user journey across systems and have ideas about how to make it less hard.

Proficiency in JavaScript or TypeScript and SQL (required). Python is a strong asset. Familiarity with Snowflake, Looker, or similar warehouse and BI tooling is helpful; you won't own that layer, but you'll need a shared vocabulary with the teams that do.

Comfort working with AI tools as part of your day-to-day workflow. We're a team that embraces AI to work smarter, and we expect the same from the people we hire.