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The company is looking to establish a foundation for clients to expand their cloud footprint and further leverage AI and ML technologies by developing and executing a data management strategy across a complex platform and AI tooling ecosystem, multiple disparate data sources, data governance processes, data domains, and teams.

Requirements

• 6+ years of experience delivering enterprise-scale solutions within government regulated environments, including data management or governance initiatives
• Experience establishing enterprise-wide agile processes and standards that drive master data and metadata management
• Experience working with AI technology stack and practices
• Knowledge of data management principles, methodologies, and best practices, including data architecture, data quality, metadata management, and master data management
• Experience with modern Cloud computing technologies, including AWS or Azure
• AWS, Google Cloud, or Microsoft Azure Certification
• Project Management Professional Certification

Responsibilities

• design strategies to deploy processes for continuous data management and AI governance
• designing and establishing robust data management structures and models to ensure the integrity, availability, and security of our data assets
• operate on teams with substantial latitude for unreviewed action or decision and supervise employees in technical competencies
• serve as a point of escalation for governance, data quality, and protection issues
• work closely with product teams to improve the quality and value of core data assets
• respond to regulatory protection requirements
• support the strategic requirements of the department

Other

• Experience managing dispersed teams and collaborating with top-level clients
• Ability to collaborate effectively across departments and influence decision-making at all levels of the organization
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
• Bachelor’s degree
• Experience improving processes and efficiencies in data and team management