Senior Analytics Engineer, Product

Inato·PARIS OFFICE or REMOTE FROM FRANCERemotesenior

In short

→Ingeniero de análisis senior que construye productos de datos para equipos de producto, CS y sponsors.
→Enfocado en autogestión de datos a escala: capa semántica, pipelines y dashboards en tiempo real.
→Destaca la integración de IA para acelerar el trabajo y escalar el equipo en crecimiento.

No se requiere nivel de inglés.

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What they ask for

✓4+ años como Analytics Engineer o rol híbrido con fuerte propiedad de datos.
✓Habilidades sólidas en dbt y modelado en warehouse (BigQuery).
✓Historial comprobado de entregar productos de datos desde definición hasta adopción.
✓Mentalidad de producto: enfocarse en el problema del usuario, no en el SQL.
✓Comunicación clara con stakeholders no técnicos.
✓Capacidad de operar con ambigüedad: convertir dolores operativos vagos en activos de datos.

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Who should you write to at Inato?

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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 parts of data work that don't need a human in the loop so the team can keep pace as new offerings multiply and Inato grows. The data team is pioneering AI-enablement internally, and this role is at the front of that. What success looks like By 3 months: You own at least one new-offering data pipeline end-to-end. Corresponding data points are available for self-service, and new metric definitions are live. You've automated at least one internal process using AI. By 6 months: At least three user-facing dashboards or data streams are live. Requirements Must-have 4+ years as an Analytics Engineer, or in a hybrid data engineer/analyst role with strong analytics engineering ownership. Strong dbt + warehouse modeling skills (we use BigQuery). Track record of owning data products end-to-end: definition → ship → measurable adoption. A genuine product mindset — you start from the user's problem, not from the SQL. Excellent written and verbal communication with non-data stakeholders. Comfort navigating ambiguity — you can turn a vague operational pain into a working data asset without a fully-specified ticket. Nice-to-have Fluency with AI-assisted tooling (Claude Code, Claude Cowork, Hex AI) and a habit of using it to ship faster. Experience building production-grade company dashboards. Domain exposure to healthcare, clinical trials, or other regulated industries. Working style You're impact-driven and pragmatic — you instinctively reach for the shortest path to the user's need.

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