MDM Data Quality Analyst- W2

Job Description

Job Description

We are seeking an experienced MDM Data Quality Analyst to support Master Data Management services for the Health and Human Services Innovation Incubator (HHSi2) project. This role will focus on data quality analysis, data profiling, business and technical requirements, testing, validation, and data governance activities supporting a unified cross-agency client/member view across State programs.

The selected candidate will work under the guidance of the MDM Technical Lead to perform data analysis, data quality assessments, testing, requirements gathering, user acceptance testing (UAT) support, SQL analysis, and validation activities to ensure reliable and accurate MDM operations.



 

Key Responsibilities

· Developing and maintaining complex SQL queries to support MDM solutions.

· Supporting SQL analysis, data validation, and data analysis reporting activities for MDM solutions.
· Collaborate with project teams supporting database objects such as tables, stored procedures, and views for MDM.
· Performing script execution, maintaining, developing, and modifying existing programs to meet system and design specifications.
· Participating in unit, integration, and system testing

· Performing data profiling and quality review and analysis

· Improving the delivery and management of health and human services programs by utilizing data analytics and quality reviews
· Gathering business requirements and preparing analyses based on information from internal and external sources to evaluate and demonstrate effectiveness and efficiency supporting projects and change requests.
· Participating in project discussions to document and recommend alternative technical solutions or requirements.

 
· Perform data quality assessments and document findings, recommendations, and remediation opportunities.
· Analyze data anomalies, matching issues, and client/member record quality concerns.

· Support data governance and data stewardship activities.

· Assist users during User Acceptance Testing (UAT) and production validation.

 
Required Qualifications

· 5+ years of experience in data analysis, data quality, MDM, business analysis, data governance, and data management.
· Experience working with MDM platforms such as Informatica MDM.

· Experience gathering and documenting business and technical requirements.

· Experience in performing data profiling, data validation, testing, reconciliation, and data quality analysis.
· Experience supporting QA, UAT, or system testing activities.

· SQL experience, with large MDM and large relational DBMS.

· Experience with data quality, matching, unique client/member identifier, standardization, reconciliation, and data governance concepts.
· Strong analytical, problem-solving, and data validation skills.

· Experience supporting MDM operations, issue resolution, testing activities, and SDLC delivery.

 
· Bachelor’s degree in computer science, Data Analytics, Information Systems, Engineering, or equivalent experience.

Preferred Qualifications

· Experience working in other MDM tools including Cloud-native MDM solutions.

· Experience working in State Government, public sector, or regulated environments.

· Experience with Agile/Scrum Sprint development and iterative/incremental delivery.

· Experience with healthcare, Medicaid, claims, eligibility, provider, or Health and Human Services data.
· Exposure to Python scripting for automation, testing, data validation, or profiling activities.
· Exposure to interoperability formats such as X12, EDI, XML, JSON, APIs, or HL7/FHIR.

· Exposure to cloud data platforms or modernization initiatives such as Azure, ADF, Databricks, Snowflake, Data Lake, or comparable technologies is a plus.
· Experience with on-prem-to-cloud migration, MDM modernization, or EDW / ETL modernization initiatives.
· Exposure to automation, AI/ML, GenAI, or LLM-assisted engineering for development, testing, documentation, profiling, or data quality is a plus.
· Ability to operate in a telecommute environment and matrix organization with minimal direction.