Analytics Engineering Lead

Novellia

About The Position

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.

Requirements

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, BigQuery, 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 communicator who can translate complex technical concepts for non-technical stakeholders
Proven ability to operate effectively in ambiguous, fast-moving environments
Builds well-documented, maintainable systems with a focus on long-term scalability
Leverages AI tooling to improve system design, accelerate documentation, and automate repetitive workflows

Nice To Haves

Experience with natural language processing (NLP) techniques and tools for analyzing unstructured text data.
Knowledge of distributed computing frameworks (e.g., Spark, Hadoop) and big data processing technologies.
Familiarity with time-series data analysis and forecasting techniques.
Contributions to open-source projects or active participation in the developer community.
Familiarity with healthcare data formats like FHIR and CCDA.

Responsibilities

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