Job Description
We're assisting one of our tech clients in the life sciences industry as they hire an Analytics Engineer . In this role, you’ll design and maintain core data models, pipelines, and reporting infrastructure — ensuring that the right people have access to clean, trustworthy, decision-grade data.
This is a highly cross-functional role with visibility across product, ops, growth, and leadership. You’ll help define analytics engineering practices, scale the data stack, and shape how the company makes better, faster decisions.
What you’ll do
- Build and maintain core data models that power internal analytics and client-facing insights
- Design and operate pipelines that transform raw data into analytics-ready tables
- Create dashboards and reporting tools that drive visibility across product, ops, and GTM
- Define and enforce metric consistency across teams (business KPIs, product usage definitions, etc.)
- Improve and scale the analytics stack (GCP BigQuery, Dataform, Fivetran, Postgres, etc.)
- Partner with stakeholders to understand data needs and translate them into reliable systems
- Contribute to internal data culture through documentation, education, and code standards
What we’re looking for
2–6 years of experience in analytics engineering, data engineering, or technical data analysis with production ownership
Strong SQL and Python skills, with experience in modern data stacks (dbt, Fivetran, Airflow, BigQuery, Postgres, Metabase)A low-ego, ownership mindset — hungry to learn, comfortable with autonomy, and motivated by impact