Azure DataOps Engineer / Azure Data Engineer *** Direct Client ***

DataOps Engineer / Azure Data Engineer (Public Health Data Modernization)

Location: Remote
Position Type: Contract (15 months with multi-year extension options)

Prior experience health care data modernization projects for state projects is highly desired

Job Summary:
We are seeking a highly skilled DataOps Engineer to lead the operationalization of a large-scale public health data infrastructure modernization initiative. This role is critical in establishing a sustainable, staff-owned DataOps foundation to improve the quality, reliability, and usability of state-wide health data. You will work at the intersection of data engineering, quality assurance, and governance, utilizing a modern cloud stack centered on Azure DevOps, Azure Databricks, and AWS Data Lake architectures.

The ideal candidate is not just a technical expert but also a mentor who can perform hands-on co-development with internal teams to build durable organizational capacity.

Key Responsibilities:

• Data Quality & Statistical Process Control (SPC): Develop and implement governed, version-controlled downstream Data Quality (DQ) rules and validation frameworks. Establish SPC monitoring for data volumes, timeliness, and distributions, including AI-assisted anomaly detection.
• Infrastructure & Pipeline Support: Translate downstream requirements into actionable specifications for upstream ingestion teams. Maintain operational performance metrics and observability dashboards.
• Data Governance & Metadata: Build and maintain data glossaries, catalogs, and end-to-end lineage visualizations within established governance tools. Define data contract requirements for external vendors, including schema expectations and QA thresholds.
• Analytics & BI Enablement: Develop governed Power BI semantic models (Cost, Quality, Access) and standardized dashboards with integrated DQ/SPC overlays.
• Organizational Enablement: Lead role-based training through active co-building sessions. Document all processes, runbooks, and SOPs as living Wikis within Azure DevOps to ensure long-term sustainability.

Required Technical Stack:

• Platform: Azure DevOps (Boards, Repos, Pipelines, Wikis).
• Data Engineering: Azure Databricks and AWS Data Lake (Medallion Architecture).
• Visualization: Power BI (DAX, RLS, semantic modeling).
• Automation: Power Automate and SharePoint integration.
• Architecture: Experience with native AWS services and complex data ingestion pipelines.

Preferred Qualifications:

• Certifications: Microsoft Certified: Azure Data Engineer Associate, Power BI Data Analyst Associate (PL-300), or Databricks Data Engineer Professional.
• Domain Expertise: Prior experience with healthcare data infrastructure (e.g., APCD, Medicaid, or clinical datasets).
• Management: DAMA CDMP, Lean Six Sigma, or Prosci Change Practitioner certifications.
• Agile: SAFe Practitioner or Scrum Master (CSM/PSM).

DataOps Engineer, Azure Data Engineer, Databricks, Azure DevOps Pipelines, Power BI Developer, Healthcare Data Analytics, AWS Data Lake, Medallion Architecture, Data Governance, Statistical Process Control, Metadata Management, Data Quality Engineering, AI Anomaly Detection, Semantic Modeling, DAX, SQL, Python, Public Health IT, Data Lineage, CDMP.