Senior Analytics Engineer

About the role

As a Senior Analytics Engineer you will partner with analysts, data engineers and business teams to design, build and maintain scalable data models that power reliable insights, experimentation and performance tracking for a fast‑growing AI‑driven healthcare platform.

Key responsibilities

• Design, build and maintain data pipelines on AWS and Azure, ensuring accuracy, consistency and trust.
• Collaborate with Clinical AI, LLMOps and Applied AI engineers to bring LLM‑powered data enrichment into production.
• Develop product event tracking and contribute to customer‑facing data products such as the analytical API and health‑system data shares.
• Improve self‑service data access via dashboards and reverse ETL to tools like Braze and HubSpot.
• Champion data quality, testing, documentation and governance across analytics workflows.

Required profile

• 3–5 years of experience in analytics engineering, data engineering or a similar data‑focused role in a fast‑paced or high‑growth environment.
• Strong proficiency in SQL and ability to transform complex data for analysis, reporting and product use cases.
• Working knowledge of Python and PySpark.
• Experience with modern data platforms and workflows (e.g., dbt, Databricks, Airflow, Snowplow, reverse ETL or BI tools).
• Interest in AI and LLM workloads and experience handling sensitive health data (PHI/PII).

Required skills

• SQL
• Python
• PySpark
• dbt
• Databricks
• Airflow
• Snowplow
• Omni (BI tool)
• AWS
• Azure

What we offer

• $1,000 annual learning and development budget
• $150/month health and wellness allowance
• $500 home office budget
• 26 weeks paid primary parental leave and 18 weeks paid secondary parental leave
• Fertility support up to $10,000
• Four weeks of work‑from‑anywhere per year
• Equity participation