Analytics Engineering Lead

About Novellia

Novellia is the first and only company that lets anyone in the US gain access to nearly a decade of their health data in under 30 seconds, 100% free. All your health records, across doctors, in one place, always up to date.

We are the only patient‑powered real‑world data platform delivering comprehensive, patient‑authorized longitudinal health insights to accelerate biopharma innovation. Unlike traditional RWD providers who offer fragmented institutional data, we empower patients to access 15+ years of their health records for free, then transform these complete health journeys into fit‑for‑purpose datasets for evidence generation, regulatory submissions, and market access.

We’re growing 5x YoY with top pharma partners. Our data have been published with leading scientific organizations such as ASCO and SABCS/AACR, and we are backed by tier‑1 investors including Spark Capital, Khosla Ventures, Bling Capital, and more.

We are seeking an experienced Analytics Engineer to own and scale Novellia's analytics engineering function. Title — whether Senior, Lead, or Staff — will reflect the right candidate's experience and scope.

This role is deeply technical. You will architect, build, and maintain the data models, pipelines, and infrastructure that power our research, product, and commercial work. You will report directly to the CTO and have end‑to‑end ownership of analytics engineering. At the same time, this is not a siloed role. You will work closely with Engineering, Data Science, and our Commercial team (Sales, Client Solutions, Marketing) to ensure our data is clean, reliable, research‑ready, and aligned with customer needs.

You should also be comfortable engaging directly with clients when needed — whether that’s providing technical context alongside our Commercial team, or answering pointed questions from our biopharma partners. This role will also partner closely with the Senior Data Analytics Engineer, Commercial Team, who owns client‑facing analytics and insight delivery — ensuring that the data infrastructure you build directly powers the work our partners rely on.

We are a fast‑growing Series A company. That means ambiguity, changing priorities, and high standards. The right person thrives in that environment — bringing rigor, initiative, and a calm, collaborative approach to solving complex problems.

• Develop a deep understanding of our data infrastructure and identify opportunities for improvement

• Ensure models and pipelines are well‑documented, reproducible, and built for scale

• Establish clear standards and processes that make it easy for others to build on your work

• Build strong working relationships with cross‑functional stakeholders and become a trusted technical partner

• Contribute to a culture of technical excellence and collaborative problem‑solving

• Design, implement, and manage scalable data pipelines and analytics platforms.

• Build and maintain dbt models to support customer projects and internal decision making.

• Work with internal stakeholders to ensure data products are research‑ready and aligned with customer needs

• Implement and manage data instrumentation and product analytics tooling (e.g. Mixpanel) to ensure accurate tracking and reporting

• Identify opportunities for optimizing data workflows and proactively address technical debt.

• Partner with Engineering, Data Science, and Commercial teams to translate business and client needs into reliable, scalable data solutions

• 5+ years of experience in data engineering or analytics roles in a startup or high‑growth environment.

• Proficiency in SQL and experience with dbt for data modeling and transformations.

• Strong experience with modern data warehouse platforms (Snowflake, Big Query, Redshift)

• Strong understanding of data architecture, ETL processes, and pipeline management.

• Proven ability to manage and own data products end‑to‑end, ideally from scratch.

• Experience with cloud platforms (AWS, GCP, etc.) for data storage and processing.

• Familiarity with product analytics tooling (e.g. Mixpanel) and modern BI tools (e.g. Looker, Tableau, Metabase)

• Clear…