Position Summary:
The Data Quality Engineer is responsible for designing, developing, documenting, and performing data quality checks across all data assets. That includes ETL jobs, reports, dashboards, and data pipelines. The primary goal for this role is to ensure high quality of data delivered to internal & external stakeholders and customers. Validation of data in data repositories against data from source systems and validation of metrics and data in reports/dashboards against data in the repositories is a key responsibility. Principle responsibilities are to ensure data assets are consistently accurate for users.
This person will be required to use logical, physical, and canonical models, possess a strong SQL background, ETL transformations and to build systems to support data analytics. They will have In-depth working knowledge of RDBMS and cloud infrastructure. They will be adept at clinical & payor data exchange with a preference toward FHIR and SMART on FHIR. Candidates with experience in FHIR Standards will be given preference.

Minimum Requirements:
5+ years of data quality assurance & engineering experience is required.
5+ years of healthcare experience is required.
SAFe (Scaled Agile Framework) or Agile experience required.
Understanding of database architecture, modeling standards.
Extract, Transform, Load (ETL) experience is required.
Strong understanding of the SDLC methodologies.
Experience with Microsoft Office & Azure cloud products.
Travel to client site on rare occasions under mutual agreement.

Education/Licenses/Certifications:
Bachelor's degree in Computer Science or related field.

Position Type: Full-Time Regular
Full Time Employee: Yes
Primary Shift: Day
Work Schedule: day