10–15 years in data governance or data stewardship, including 3–5 years focused on AI/ML data
Experience working with enterprise-scale data platforms and large organizations
Technical Skills
Strong understanding of AI/ML data pipelines: ingestion, labeling, feature engineering, model training
Familiarity with MLOps tools such as MLflow, Azure ML, SageMaker, Databricks
Experience with data governance/catalog tools (Collibra, Atlan, Alation, Informatica)
Working knowledge of SQL and basic Python
Experience with cloud data platforms (Snowflake, Databricks, BigQuery, Redshift)
Understanding of feature stores, model registries, and data versioning
Governance & Compliance
Ability to develop and enforce AI data governance policies
Knowledge of GDPR, CCPA, and responsible AI guidelines
Experience conducting bias reviews, data quality checks, and maintaining data lineage
Business & Leadership Skills
Strong analytical thinking with the ability to translate insights into recommendations
Excellent communication skills across executive and technical teams
Proven ability to lead cross‑functional governance discussions and drive adoption
Experience in process improvement and implementing governance workflows
Soft Skills
Detail‑oriented, organized, and capable of managing multiple priorities
Strong stakeholder‑management and relationship‑building skills
Self‑motivated, adaptable, and comfortable working in a rapidly evolving AI environment