Data Integration Engineer

Thyme Care Thyme Care · Healthcare · Remote · Data Science

Data Integration Engineer on the Data Ingestion & Care Enablement (DICE) team responsible for ensuring reliable flow of partner and vendor data into Thyme Care. This role involves collaborating with Product Managers and Data teammates to support data ingestion, debug failures, and improve reliability through tests, monitoring, and data contracts. The engineer will work with healthcare data sources, build data models and pipelines using SQL, dbt, and Python, and automate processes using Dagster and GitHub Actions.

What you'd actually do

  1. Gain a deep understanding of our data platform and contribute to improving our data models and pipelines using SQL, dbt, and python (generally data-focused packages, e.g., pandas, polars)
  2. Support ingestion of a wide range of healthcare-related sources (claims, eligibility, prior auth, ADT, etc.) by
  3. Collaborate with data scientist deal owners and internal stakeholders to turn messy, ambiguous requirements into concrete mapping/validation logic and durable data contracts
  4. Use Dagster and GitHub Actions to orchestrate and automate the early stages of our data pipelines, improving run reliability and reducing manual intervention
  5. Work hands-on with raw data using Jupyter Notebooks in Databricks to investigate data issues, validate assumptions, and unblock processing

Skills

Required

  • Strong SQL skills
  • Familiarity with dbt
  • Working knowledge of Python for data investigation in notebooks
  • Experience operating data pipelines: debugging failures, tracing issues across systems, and communicating clearly about root cause and mitigation
  • Experience with testing and data quality: writing and maintaining tests and using failures/alerts to drive durable fixes
  • Responsiveness and the ability to stay calm and organized when triaging failing ingestion runs or pipelines
  • Willingness to learn new domains and tools quickly
  • The ability to engage technical and non-technical stakeholders to explain what’s happening in our pipelines and identify opportunities to improve transparency and alerting

Nice to have

  • healthcare data exposure (claims/eligibility/ADT/etc.)

What the JD emphasized

  • debugging failures
  • data contracts
  • testing and data quality
  • triage failing ingestion runs or pipelines
  • reliability