• Define and align on critical business metrics by collaborating closely with department leaders. • Analyze and master data structures across various source systems, including Salesforce, NetSuite, and internal databases. • Leverage ETL and streaming technologies, such as Apache Airflow and Kafka Connect, to facilitate seamless data transfers. • Build and maintain a data warehouse (e.g., BigQuery). • Use business intelligence tools (e.g., Looker) to establish data models and create.

• Join a mission-driven health technology company building a global evidence network • Part of a core data engineering team responsible for designing and operating pipelines • Ingest, transform, and standardize real-world health data • Translate complex source data structures into recognized healthcare data standards (FHIR, OMOP-CDM) • Ensure data quality, security, and scalability across the platform • Work in a fast-paced, engineering-led environment

• Own the blueprint for the next-generation Jellyfish data platform. • Design and automate strict, code-driven environment isolation boundaries. • Modernize workflow orchestration and distributed compute engines. • Partner with application teams to ensure secure, cached API layers. • Build and maintain granular data-quality monitors and cost-allocation frameworks.

• Write clean, modular Python and optimized SQL for data transformations. • Manage and tune workflow orchestration engines (like Prefect or Dagster). • Use Terraform for infrastructure deployment and management. • Collaborate with developers for API and caching integration. • Participate in incident response rotation for pipeline issues.