MDM Data Quality Analyst
RemoteUnited States
United StatesRemoteFull TimeSmall
Full TimeSmall
Job Summary
Develop and maintain complex SQL queries to support MDM solutions, performing data profiling, quality reviews, and anomaly analysis on cross-agency resident records. Collaborate with project teams to document remediation recommendations, execute testing, and support User Acceptance Testing for data governance initiatives. Analyze matching issues and client/member record quality concerns to improve health and human services program delivery. Work under the guidance of the MDM Technical Lead to evaluate business requirements and recommend technical solutions for statewide data modernization.
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 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
Desired 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, or Data Lake
- 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
- Ability to operate in a telecommute environment and matrix organization with minimal direction
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