Data Engineer

Who you are

• 1-2+ years of experience in data engineering, ETL development, or cloud-based data orchestration. 1-2+ years of experience in data science, analytics, or applied research, IF hold a PHD/published research
• Strong proficiency in Python and SQL
• Hands-on experience with workflow orchestration tools (Airflow, Prefect, or similar)
• Experience with cloud platforms and services (AWS, Azure, GCP familiarity is a plus)
• Experience building on Databricks and working with distributed processing frameworks (Apache Spark, Dask, or similar)
• Solid understanding of data validation, observability, testing, and production best practices
• Experience with healthcare, imaging, or PHI-sensitive data is a strong plus
• Strong communication and documentation skills; comfortable working across technical teams
• You are an experienced data engineer who enjoys building systems that scale and last.
• You’re comfortable working across a wide range of data types and tools, and you approach complex problems with curiosity and pragmatism.
• You’re collaborative, thoughtful, and proactive, with a strong sense of ownership and care for the people who depend on the data you build. Ideally, you come from data engineering or software background in healthcare, biotech, or other high-trust data environments

What the job involves

• As a Data Engineer, you will design, build, and scale the core data infrastructure that powers Function Health’s imaging, analytics, and AI ecosystems. You’ll work closely with the Data, AI, and R&D teams to orchestrate secure, reliable, and compliant pipelines across a wide range of healthcare data types
• This role focuses on building robust orchestration and cloud-native data systems (Airflow, AWS, Databricks) that support high-volume, heterogeneous datasets — from DICOM imaging to biomarkers, reports, and other structured and unstructured health data. You’ll help ensure that these systems are performant, scalable, and production-ready as our platform and data footprint continue to grow
• You will be working closely with the Data team and AI engineering team and reporting to Radhika Tibrewala
• Design and operate scalable data pipelines and orchestration systems supporting imaging and biomarker data (e.g., Airflow, cloud services, distributed compute platforms)
• Contribute to PHI-safe, compliant data infrastructure aligned with healthcare standards (HIPAA, GDPR, etc.)
• Enhance performance and fault-tolerance across distributed data workflows
• Partner with the data management lead to integrate DICOM and data pipelines into the broader data lake and analytics stack
• Implement robust data validation, observability, and monitoring systems for production pipelines
• Collaborate with data science, ML, and product teams to ensure data reliability and accessibility
• Support automated ingestion, transformation, cataloging, and access patterns for downstream analytics and ML use cases

Benefits

• Choose your own holidays
• 401k Match
• Health Insurance