Data Engineer

Role overview

This role builds the data foundation for a healthcare advocacy platform that helps patients navigate a complex system by pairing them with expert advocates. As an early member of a small, fast-moving data team, the engineer will architect pipelines, set engineering standards, and own a FastAPI data service that powers data-driven features inside the application. The work spans raw ingestion through modeling, with a strong emphasis on reliability, security, and the handling of sensitive medical data.

Responsibilities

- Design, build, and optimize scalable data pipelines using Airflow, Python, dbt, and Snowflake, replacing brittle manual processes with resilient automated workflows. - Manage and evolve cloud infrastructure across AWS or GCP using Terraform, ensuring the platform is reproducible, secure, and scalable. - Write clean, production-grade Python code and champion engineering best practices including code reviews, testing, and CI/CD. - Collaborate with analysts to design performant SQL transformations and data models in Snowflake, ideally through dbt. - Implement observability and monitoring to catch data quality issues before they reach stakeholders. - Partner with data analysts and product managers to translate data needs into reliable data products. - Own the FastAPI data service end to end, including endpoint design, performance, deployment, monitoring, and reliability for dependent product teams.

Requirements

- Strong Python proficiency with the ability to write modular, testable, and efficient code for data processing and automation. - Advanced SQL skills and deep expertise in cloud data warehousing, Snowflake preferred, with attention to performance and cost. - Proven experience building and maintaining complex workflows in Airflow or a comparable orchestrator. - Familiarity with Terraform and AWS or GCP for provisioning and managing pipeline infrastructure. - Experience handling sensitive medical data, including PHI and PII, with secure access controls such as RBAC and adherence to strict governance standards. - A self-starter mindset comfortable with ambiguity, willing to take ownership and wear many hats in a high-growth environment. - Ability to translate complex technical challenges into clear options for non-technical stakeholders.

Nice to have

- Hands-on dbt experience for managing transformations and implementing testing and documentation standards. - Background in healthcare data standards or strictly regulated HIPAA environments. - Experience with Docker and Kubernetes for deploying data applications. - Exposure to backend service or API development (for example FastAPI or Flask) or to MLOps practices such as model deployment, versioning, and monitoring.

Benefits and work setup

- Applicants must be based in the United States. - Stack includes Snowflake, Postgres, Airflow, Terraform, AWS or GCP, dbt, SQL, Python, and a team-owned FastAPI data service.