Senior Analytics Engineer, Product

United States Digital Space LLC; Paris; Hybride; EUR 65 000 - 80 000; Plein temps

Avantages offerts par ce poste

Remote-first policy

Office in Paris (Grands Boulevards)

Top-of-the-line equipment

RTT – compensatory time

Health insurance (Benefiz, 100% paid)

Meal vouchers (Swile)

Wellpass activity perks

Free books & learning materials

Résumé du poste

Inato is hiring a Senior Analytics Engineer, Product to own how data moves from our platform into the hands of product squads, CS and Marketing teams, sponsors and sites. You will 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 the Data Director and collaborate with PMs, engineers, designers, and other stakeholders.

Qualifications

• 4+ years in analytics engineering or hybrid data engineer/analyst role with ownership of analytics outcomes.
• Strong dbt + data warehouse modelling skills (BigQuery).
• Proven track record of end-to-end data products: definition → ship → adoption.
• User-centric mindset: start from user problems, not just SQL.
• Excellent written and verbal communication with non-data stakeholders.
• Ability to navigate ambiguity and translate pains into data assets without strict tickets.

Responsabilités

• Own end-to-end data pipelines and data products used by product squads, CS, Marketing, sponsors and sites.
• Define metrics and build the semantic layer powering AI-driven self-service in Hex.
• Develop and ship user-facing dashboards and data streams.
• Collaborate with cross-functional teams to translate operational pain into working data assets.
• Leverage AI-assisted tooling to accelerate data delivery while maintaining quality.

Connaissances

Analytics engineering

dbt

BigQuery

Communication

Ambiguity handling

Outils

Airbyte

Dagster

Hex

Description du poste

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 endeavour: 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.

The company 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 the company'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 the company 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. You’re systematic: you'd rather improve the system than re-fix the same symptom. You're satisfied shipping the 80% solution at 20% of the effort, then iterating on it. You're equally comfortable in a stakeholder conversation, a dbt PR, and a quick prototype.

You’ll thrive here if your career arc looks something like: started as an analyst or PM, moved up the stack toward analytics engineering or data product, have lived in start-ups or scale-ups where you owned a meaningful slice of the data value chain end-to-end, and have shipped complex projects with measurable end-user value.

Location and Compensation

• France-based, remote-first. Office available in Grands Boulevards, Paris if you want to use it.

• Base salary range: 65,000€ – 80,000€, plus equity. No individual variable bonus.

Why this role, why now

The company is in a phase of rapid growth driven by new product offerings, and the data team is one of the functions directly responsible for proving and scaling that value. You'll have a direct line to the VP Product, real ownership from day one, and a small senior team around you. The company is leaning hard into AI-enablement, and the data team is pioneering it internally — there's a clear path to Lead or Staff Analytics engineer, or Data Product Manager within 2–3 years as our data-as-a-product surface grows.

Perks

• Remote-first philosophy & flexible hours

• Amazing office in Grands Boulevards, Paris where you can meet with colleagues if this is important for you

• Top-of-the-line equipments

• Compensatory time (RTT)

• Health insurance (Benefiz, 100% paid by the company)

• Meal vouchers (Swile)

• Contribution to healthy activities (Wellpass, ex-Gymlib)

• Free books & learning material

Compensation

€65K – €80K Offers Equity