Enterprise Data & AI Lead - Remote

Job Location: This position is remote within the United States.

What You'll Be Doing

• Lead enterprise data, analytics, governance, and AI-enabled capability delivery across a complex federal technology environment.
• Develop and implement data governance policies, standards, operating procedures, approval workflows, and accountability models.
• Establish and maintain data portfolio management practices, including prioritization, project intake, resource planning, risk tracking, milestone reporting, and performance measurement.
• Lead the design and implementation of scalable data architecture, including data pipelines, data lakes, data warehouses, data marts, data catalogs, metadata repositories, and data lineage capabilities.
• Define and enforce data quality standards, validation rules, data dictionaries, scorecards, issue management workflows, and continuous monitoring processes.
• Guide development of analytics products, dashboards, reports, and visualization tools that provide operational insight and support executive decision-making.
• Support advanced analytics capabilities, including statistical analysis, predictive modeling, trend analysis, root cause analysis, and AI-enabled analytics.
• Ensure data sharing, API integration, and data access models are secure, governed, auditable, and aligned with privacy, cybersecurity, and compliance requirements.
• Partner with cybersecurity, engineering, product, and program management teams to align data platforms, applications, integrations, and analytics capabilities with enterprise standards.
• Establish reusable templates, frameworks, data models, ETL/ELT patterns, documentation repositories, and project management toolkits for data initiatives.
• Support training, documentation, and knowledge transfer to improve user adoption and long-term sustainment of data tools, dashboards, and data management practices.
• Monitor data quality, data usage, access patterns, and analytics adoption to identify risks, improvement opportunities, and operational blind spots.

What You Must Have

• Bachelor's Degree in Data Science, Computer Science, Information Systems, Engineering, Statistics, Mathematics, Business Analytics, or a related field.
• One active data, cloud, analytics, AI/ML, or data governance certification, such as CDMP, DAMA, AWS/Azure/Google Cloud Platform data certification, Microsoft Power BI certification, Databricks, Snowflake, or equivalent.
• 10+ years of experience leading enterprise data, analytics, data governance, data engineering, data architecture, or AI-enabled analytics initiatives.
• 8+ years of experience designing, implementing, or managing enterprise data platforms, data pipelines, data warehouses, data lakes, data marts, data catalogs, or metadata management capabilities.
• U.S. Citizenship required due to federal contract requirements.
• Must be able to obtain and maintain a Public Trust clearance.

Preferred Qualifications

• 5+ years of experience establishing data governance policies, standards, stewardship models, data quality frameworks, data dictionaries, lineage practices, or data management operating models.
• 5+ years of experience delivering analytics products, dashboards, reporting capabilities, data visualizations, or executive decision-support tools.
• 5+ years of experience working in federal, public sector, healthcare, life sciences, or other regulated environments with formal privacy, security, or compliance requirements.
• 3+ years of experience supporting AI-enabled analytics, predictive modeling, machine learning workflows, anomaly detection, or advanced analytics use cases.
• 3+ years of experience with data integration methods, including APIs, ETL/ELT pipelines, data orchestration, batch processing, real-time ingestion, or change data capture.
• 3+ years of experience using data visualization, analytics, or business intelligence tools such as Power BI, Tableau, QuickSight, Looker, Palantir Foundry, or similar platforms.
• 3+ years of experience with cloud data services on AWS, Microsoft Azure, Google Cloud Platform, or similar cloud environments.
• Experience supporting HHS, NIH, FDA, CMS, CDC, or other health-focused federal environments.
• Experience building or supporting Chief Data Office functions, enterprise data governance programs, or data portfolio management organizations.
• Experience with data privacy, data protection, data classification, DLP, encryption, RBAC, ABAC, just-in-time access, or audit logging requirements.
• Experience aligning data capabilities with NIST, FISMA, HIPAA, FedRAMP, GDPR, or other security and compliance frameworks.
• Experience developing data catalogs, metadata management approaches, lineage models, data quality scorecards, data issue repositories, and data stewardship workflows.
• Experience implementing AI governance, responsible AI practices, model monitoring, explainability, human-in-the-loop review, or secure AI-enabled analytics.
• Experience with SQL, Python, R, Databricks, Snowflake, Redshift, BigQuery, Synapse, Dataverse, or similar data platforms and tools.
• Additional cloud, data, analytics, AI/ML, cybersecurity, Agile, ITIL, DAMA, CDMP, or project management certification.