Senior Data Quality Analyst — AI & Analytics Liaison

Sistema Technologies Inc.; Austin (TX); On-site; USD 80,000 - 115,000; Full time

Job summary

The Texas Health and Human Services Commission (HHSC) is seeking a senior business data quality analyst in Austin, TX. The role acts as a critical liaison between IT and non-technical program staff, focusing on data profiling, quality measures, and AI-related data validation to support analytical reporting and strategic decision-making.

Responsibilities include translating data findings for end-users, integrating data from multiple sources, and developing visualizations to depict data quality.

Qualifications

• Strong SQL for data extraction, profiling and validation.
• Experience translating data findings for non-technical stakeholders.
• Experience with data governance and data quality principles.
• Ability to explain data limitations and results to leadership.
• Familiarity with AI data quality considerations and prompting is a plus.

Responsibilities

• Serve as a senior liaison between IT and program staff on data quality issues.
• Extract, integrate, and analyze data from multiple sources to support analytics needs.
• Create visualizations showing data quality profiles for analytics initiatives.
• Provide SME guidance on validating AI outputs and mitigating hallucinations.
• Develop training and documentation to promote data literacy across the organization.
• Collaborate with data engineering, IT, and program teams to address data inconsistencies.

Skills

SQL

Data profiling

Data governance

Data analysis

Communication

Job description

The Texas Health and Human Services Commission (HHSC) is seeking a senior business data quality analyst in Austin, TX. The role acts as a critical liaison between IT and non-technical program staff, focusing on data profiling, quality measures, and AI-related data validation to support analytical reporting and strategic decision-making.

Responsibilities include translating data findings for end-users, integrating data from multiple sources, and developing visualizations to depict data quality.