Data Engineer (Governance and QA)

TL;DR

Data Engineer (Governance and QA): Building and optimizing automated data quality frameworks and reporting pipelines for a healthcare specialty care platform with an accent on data governance, QA automation, and reliability. Focus on establishing deterministic logic, implementing Python-based validation frameworks, and ensuring the accuracy of outbound healthcare data products.

Location: Hybrid - Dallas, Texas (minimum 3x per week in office)

Company

A specialty care platform connecting patients with top specialists to deliver high-quality healthcare with significant cost savings for employers and their workforces.

What you will do

• Own end-to-end data quality, integrity, and reliability across staging, transformation, and outbound reporting layers.
• Implement automated data quality checks using Python-based frameworks such as dbt, Pytest, Soda, or Great Expectations.
• Define and execute the overall test strategy including unit, integration, regression, and end-to-end testing for outbound reporting.
• Integrate automated QA processes into CI/CD pipelines in partnership with Platform Engineering.
• Establish and maintain QA documentation, including test plans, validation rules, and data quality SLAs.
• Perform targeted manual validation for new report configurations and schema changes where automation is insufficient.

Requirements

• 5+ years of experience in QA Engineering, Data Engineering, or Data Quality within data-intensive or regulated environments.
• Proficiency in Python for automated testing, data validation, and quality frameworks.
• Hands-on experience with automated data quality tools (dbt tests, Pytest, Soda, Great Expectations, or similar).
• Experience working within CI/CD environments (GitHub Actions, GitLab, Jenkins, etc.).
• Strong understanding of data modeling and data architecture concepts.
• Must be based in or able to work hybrid in Dallas, Texas.

Nice to have

• Experience with healthcare datasets, including claims, eligibility, and utilization.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data platform components.
• Experience with Databricks for data processing and pipeline automation.
• Background in configuration-driven reporting or client-specific outbound file generation.

Culture & Benefits

• Comprehensive insurance: Medical, Dental, and Vision coverage.
• Financial benefits: 401k with company match and Life Insurance.
• Paid time off, including Paid Parental Leave.
• Short- and Long-Term Disability insurance.