Senior Analytics Engineer, Product

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Who We Are Inato is a Tech for Good company striving to bring clinical research to each and every patient, regardless of who they are or where they live. To do this, we are building the world's first clinical trial platform to create greater visibility, access, and engagement across a more diverse population of doctors and their patients.

Drug development is a challenging, intellectually complex, and rewarding endeavor: we enable global pharmaceutical companies to confidently partner with community-based researchers to increase patient access to the latest medical innovations. Our AI-powered platform currently offers clinical trials from leading companies to over 5,500 sites across the globe and we are well poised for growth in 2026.

We are a growing team of passionate pharmaceutical experts, software and AI engineers, professional services members, and many more—all bringing their unique perspectives to solve the challenges facing clinical research. Inato is the recent recipient of Fast Company’s Most Innovative Companies of 2024, Fierce Healthcare’s Fierce 15, and Built In's Best Places to Work 2025.

The Role We're hiring a Senior Analytics Engineer, Product to own how data moves from Inato's platform into the hands of the people who depend on it — our product squads, CS and Marketing teams, sponsors, and sites. You'll enable trusted self-service at scale, prove the value of our new product offerings faster, and ship data products directly into the user experience.

You'll report to Alexandre Halley (Data Director) and partner daily with Product squads (PMs, engineers, designers), with regular touchpoints into CS, Marketing, and Sponsor / Site Ops. Our stack includes Segment, Airbyte, Dagster, BigQuery, dbt, Hex, FullStory, and more. What you'll own Trusted self-service at scale. Own metric definitions, build the semantic layer powering our AI-driven self-service in Hex, and govern what gets exposed so non-data teams can answer their own questions confidently.

Faster value validation for new offerings. Partner with squads to translate vague operational pains (a CS workflow, a sponsor enablement gap, a prototype idea) into working data assets in days — from real-data prototype to production-grade pipeline. Data products in front of users. Own the tables consumed by the product itself, and the user-facing dashboards (embeds, custom interfaces) that sponsors, sites, and internal teams rely on day to day. Using AI to scale yourself and the team. Automate the