DHCF Medicaid Data Systems Analyst

Washington, AR - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

This role ensures the technical infrastructure remains trustworthy by leading the implementation of an Enterprise Data Catalog and managing the transition of business logic from TFS/SSIS to the Azure/Databricks environment. They act as the Metadata Architect ensuring that all raw MMIS schemas are translated into governed auditable and BI-ready assets.

A. Data Catalog Implementation & Metadata Governance

Business Glossary Ownership: Lead the implementation of the Enterprise Data Catalog (e.g. Microsoft Purview or Unity Catalog)from a functional perspective. Define and maintain the business glossary for all Medicaid data.
Data Lineage Mapping: Document and verify end-to-end data lineage from the raw MMIS source table through the transformation layer in Databricks to the final PowerBI report.
Discovery & Search: Organize the catalog so that policy analysts and actuaries can easily discover Medicaid datasets understand their sensitivity (PHI/PII) and view their update frequency.

B. Infrastructure & FinOps Support

Data Reliability Engineering: Support the infrastructure s health by monitoring Data Quality (DQ) dashboards. Alert the Senior Data Engineer if upstream MMIS schema changes cause data drift or pipeline failures.
FinOps Collaboration: Partner with the Senior Data Engineer to analyze cloud consumption. Identify unused or redundant datasets that can be purged or archived to optimize Azure storage and compute costs.
Infrastructure Validation: Verify that the Infrastructure as Code deployments (Managed by the Engineer) correctly apply the Row-Level Security (RLS) and masking rules defined by the Lead Architect.

C. Schema Transformation & Migration Support

Legacy-to-Cloud Logic Audit: Translate legacy SSIS logic stored in TFS into clear business requirements for the Engineer to rebuild in Azure Data Factory and Databricks.
Target Mapping: Take raw table schemas from the current MMIS and define the Target format for the Data Warehouse ensuring it meets the specific needs of modern BI tools.

Skill	Required / Desired	Amount	of Experience
Expert T-SQL skills for deep-dive data auditing and parity testing between legacy SQL Server and Azure Synapse.	Required	5	Years
Experience with MMIS data specifically claims (837) eligibility (270/271) and T-MSIS federal reporting.	Required	5	Years
Familiarity with TFS (for reviewing legacy logic) and Azure DevOps (for modern project tracking).	Required	5	Years
Industry certification/training in specific IT product/platform or service	Required	5	Years
5 yrs. leading advanced technology projects or service projects	Required	5	Years
Hands-on experience in specific product or IT platform	Required	5	Years
5 yrs full system engineering lifecycle	Required	5	Years
Bachelor s degree	Required
Certification in Data Governance (e.g. CDMP) or Cloud Fundamentals (e.g. Azure AZ-900).	Highly desired
Experience with Power BI or Tableau to validate that transformed data meets visualization requirements.	Highly desired
Hands-on experience with Microsoft Purview Collibra Informatica and Alation	Highly desired

A. Data Catalog Implementation & Metadata Governance

Business Glossary Ownership: Lead the implementation of the Enterprise Data Catalog (e.g. Microsoft Purview or Unity Catalog)from a functional perspective. Define and maintain the business glossary for all Medicaid data.
Data Lineage Mapping: Document and verify end-to-end data lineage from the raw MMIS source table through the transformation layer in Databricks to the final PowerBI report.
Discovery & Search: Organize the catalog so that policy analysts and actuaries can easily discover Medicaid datasets understand their sensitivity (PHI/PII) and view their update frequency.

B. Infrastructure & FinOps Support

Data Reliability Engineering: Support the infrastructure s health by monitoring Data Quality (DQ) dashboards. Alert the Senior Data Engineer if upstream MMIS schema changes cause data drift or pipeline failures.
FinOps Collaboration: Partner with the Senior Data Engineer to analyze cloud consumption. Identify unused or redundant datasets that can be purged or archived to optimize Azure storage and compute costs.
Infrastructure Validation: Verify that the Infrastructure as Code deployments (Managed by the Engineer) correctly apply the Row-Level Security (RLS) and masking rules defined by the Lead Architect.

C. Schema Transformation & Migration Support

Legacy-to-Cloud Logic Audit: Translate legacy SSIS logic stored in TFS into clear business requirements for the Engineer to rebuild in Azure Data Factory and Databricks.
Target Mapping: Take raw table schemas from the current MMIS and define the Target format for the Data Warehouse ensuring it meets the specific needs of modern BI tools.

Skill	Required / Desired	Amount	of Experience
Expert T-SQL skills for deep-dive data auditing and parity testing between legacy SQL Server and Azure Synapse.	Required	5	Years
Experience with MMIS data specifically claims (837) eligibility (270/271) and T-MSIS federal reporting.	Required	5	Years
Familiarity with TFS (for reviewing legacy logic) and Azure DevOps (for modern project tracking).	Required	5	Years
Industry certification/training in specific IT product/platform or service	Required	5	Years
5 yrs. leading advanced technology projects or service projects	Required	5	Years
Hands-on experience in specific product or IT platform	Required	5	Years
5 yrs full system engineering lifecycle	Required	5	Years
Bachelor s degree	Required
Certification in Data Governance (e.g. CDMP) or Cloud Fundamentals (e.g. Azure AZ-900).	Highly desired
Experience with Power BI or Tableau to validate that transformed data meets visualization requirements.	Highly desired
Hands-on experience with Microsoft Purview Collibra Informatica and Alation	Highly desired