The Data Governance & AI Architect will lead the design and implementation of enterprise-grade data and AI platforms, ensuring they are scalable, secure, governed, and ethically aligned.
Requirements
- Data engineering experience
- Leadership in data governance and AI architecture
- Strategic leadership in data engineering
- Technical expertise in data engineering
- Ability to bridge business needs with technical execution
- Experience with Databricks, Spark, Airflow, and Kafka
- Knowledge of data modeling standards and governance requirements
- Ability to optimize data infrastructure for performance, reliability, and cost-efficiency
- Experience with data governance teams and policy embedding
- Knowledge of regulatory compliance and internal governance initiatives
- Ability to promote data stewardship and ownership models
- Experience with AI/ML platforms, feature stores, model training environments, and deployment pipelines
- Knowledge of MLOps best practices and model lifecycle management
- Ability to ensure AI systems are designed for scalability, explainability, and ethical use
- Experience with cloud-native services such as Azure ML, AWS SageMaker, and GCP Vertex AI
- Ability to partner with cybersecurity and legal teams to ensure security and ethical standards
- Knowledge of data access, encryption, and model transparency controls
- Ability to support responsible AI practices including bias detection, fairness, and accountability
- Experience with collaboration and leadership in cross-functional teams
Benefits
- Health and Safety #1 priority
- Competitive wages
- Comprehensive health benefits
- Group 401K with company matching component
- Employee Stock Purchase Plan
- Generous paid time off
- Company paid training and tuition reimbursement
- Positive and safe work environments
- Opportunities for growth and development