Remote Enterprise Data & AI Leader

ICF Olson

United States

Remote

USD 90,000 - 152,000

Full time

3 days ago

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Job summary

ICF is seeking an experienced Chief Data Office / Data & AI Lead to steer enterprise data, analytics, governance, and AI-enabled capabilities for a complex federal technology services program. This remote, United States–based role supports design, implementation, and sustainment of data policy, standards, governance, portfolio management, architecture, data quality, and secure data access.

The successful candidate will translate mission needs into governed data assets, lead data platforms and

Qualifications

Bachelor’s degree in a data-related field.
Active data/analytics or governance certification.
10+ years leading enterprise data initiatives.
8+ years building data platforms, pipelines, warehouses, data catalogs, or metadata management.
U.S. Citizenship required; able to obtain Public Trust clearance.

Responsibilities

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 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.