Enterprise Data, AI Lead

This is a fully remote position, open to applicants in Virginia.

📋 Description

• Oversee the delivery of enterprise data, analytics, governance, and AI-driven capabilities within a complex federal technology landscape.

• Create and execute data governance policies, standards, operational procedures, approval workflows, and accountability frameworks.

• Develop and uphold data portfolio management practices, including project prioritization, intake processes, resource allocation, risk monitoring, milestone tracking, and performance assessment.

• Spearhead the design and deployment of scalable data architecture, encompassing data pipelines, data lakes, data warehouses, data marts, data catalogs, metadata repositories, and data lineage capabilities.

• Specify and implement data quality standards, validation protocols, data dictionaries, scorecards, issue management workflows, and continuous monitoring methodologies.

• Direct the creation of analytics products, dashboards, reports, and visualization tools that facilitate operational insights and support executive decision-making.

• Assist in statistical analysis, predictive modeling, trend analysis, root cause analysis, and AI-enhanced analytics.

• Guarantee that data sharing, API integration, and data access methodologies are secure, governed, auditable, and compliant with privacy, cybersecurity, and regulatory requirements.

• Collaborate with cybersecurity, engineering, product, and program management teams to ensure alignment of platforms, applications, integrations, and analytics capabilities with enterprise standards.

• Develop reusable templates, frameworks, data models, ETL/ELT patterns, documentation repositories, and project management toolkits.

• Facilitate training, documentation, and knowledge transfer initiatives to enhance the adoption and sustainability of data tools, dashboards, and data management practices.

• Track data quality, usage, access patterns, and analytics adoption to pinpoint risks, opportunities for improvement, and operational blind spots.

⛳️ Requirements

• Bachelor’s Degree in Data Science, Computer Science, Information Systems, Engineering, Statistics, Mathematics, Business Analytics, or a related discipline.

• One active certification in data, cloud, analytics, AI/ML, or data governance, such as CDMP, DAMA, AWS/Azure/GCP data certification, Microsoft Power BI certification, Databricks, Snowflake, or equivalent.

• Over 10 years of experience leading initiatives in enterprise data, analytics, data governance, data engineering, data architecture, or AI-enabled analytics.

• More than 8 years of experience in designing, implementing, or managing enterprise data platforms, data pipelines, data warehouses, data lakes, data marts, data catalogs, or metadata management capabilities.

• U.S. Citizenship is mandatory due to federal contract stipulations.

• Must have the ability to obtain and maintain a Public Trust clearance.

• Preferred: Over 5 years of experience in establishing data governance policies, standards, stewardship models, data quality frameworks, data dictionaries, lineage practices, or data management operating models.

• Preferred: More than 5 years of experience delivering analytics products, dashboards, reporting capabilities, data visualizations, or tools for executive decision support.

• Preferred: At least 5 years of experience in federal, public sector, healthcare, life sciences, or other regulated environments.

• Preferred: Over 3 years of experience in supporting AI-enabled analytics, predictive modeling, machine learning workflows, anomaly detection, or advanced analytics use cases.

• Preferred: More than 3 years of experience with APIs, ETL/ELT pipelines, data orchestration, batch processing, real-time ingestion, or change data capture.

• Preferred: At least 3 years of experience using Power BI, Tableau, QuickSight, Looker, Palantir Foundry, or similar platforms.

• Preferred: Over 3 years of experience with AWS, Microsoft Azure, Google Cloud Platform, or similar cloud environments.

• Preferred: Experience in supporting HHS, NIH, FDA, CMS, CDC, or other health-focused federal environments.

• Preferred: Familiarity with Chief Data Office functions, enterprise data governance programs, or data portfolio management organizations.

• Preferred: Knowledge of data privacy, data protection, data classification, DLP, encryption, RBAC, ABAC, just-in-time access, or audit logging.

• Preferred: Experience in aligning data capabilities with NIST, FISMA, HIPAA, FedRAMP, GDPR, or other security and compliance frameworks.

• Preferred: Experience in developing data catalogs, metadata management strategies, lineage models, data quality scorecards, data issue repositories, and data stewardship workflows.

• Preferred: Experience in implementing AI governance, responsible AI practices, model monitoring, explainability, human-in-the-loop reviews, or secure AI-enabled analytics.

• Preferred: Proficiency in SQL, Python, R, Databricks, Snowflake, Redshift, BigQuery, Synapse, Dataverse, or similar data platforms and tools.

• Preferred: Additional certifications in cloud, data, analytics, AI/ML, cybersecurity, Agile, ITIL, DAMA, CDMP, or project management.

🏝️ Benefits

• Equal opportunity employer.

• Reasonable accommodations for individuals with disabilities, disabled veterans, and those with sincerely held religious beliefs.

• Confidential accommodation support provided during the application and employment process.