AI Data Governance Lead

Job Title: AI Data Governance Lead Location: Dallas, TX (Onsite – 5 days a week, 8 AM to 4 PM) Duration: 9-month rolling contract Job Summary: We are seeking an experienced AI Data Governance Lead with strong retail domain experience to support enterprise-scale data initiatives. The ideal candidate will have deep expertise in data governance, AI/ML data lifecycle management, and working with large data platforms. This role requires strong collaboration with cross-functional teams to ensure data quality, compliance, and governance standards across AI-driven systems. Key Responsibilities: Develop and enforce data governance policies and frameworks for AI and enterprise data Manage and oversee AI/ML data pipelines including data ingestion, labeling, feature engineering, and model training processes Ensure data quality, lineage, and integrity across enterprise data platforms Conduct bias reviews and ensure responsible AI practices are followed Collaborate with engineering, data science, and business teams to implement governance workflows Work with data catalog and governance tools such as Collibra, Alation, Atlan, or Informatica Support MLOps processes using tools like MLflow, Azure ML, SageMaker, or Databricks Monitor and manage data versioning, feature stores, and model registries Ensure compliance with data regulations such as GDPR and CCPA Drive process improvements and promote best practices in data governance Lead cross-functional discussions and communicate effectively with technical and executive stakeholders Required Qualifications: Minimum 10 years of experience in data governance or data stewardship At least 3 to 5 years of experience working with AI/ML data Strong experience in retail domain is required Experience working with enterprise-scale data platforms and large organizations Strong understanding of AI/ML data pipelines and lifecycle Hands-on experience with SQL and basic knowledge of Python Experience with cloud data platforms such as Snowflake, Databricks, BigQuery, or Redshift Familiarity with MLOps tools such as MLflow, SageMaker, Azure ML, or Databricks Experience with data governance and catalog tools such as Collibra, Atlan, Alation, or Informatica Strong understanding of data compliance and governance frameworks Preferred Skills: Experience with feature stores and model lifecycle management Strong analytical and problem-solving skills Excellent communication and stakeholder management abilities Ability to work in a fast-paced and evolving AI environment