Principal Data Lead

Unissant•Washington, VA

2d•Remote

About The Position

Unissant, Inc. is seeking a Principal Data Lead to join their team and support a government client on a large, multi-year IT services program. This role is accountable for data strategy execution, data supply chain and metadata maturity leadership, trusted-data promotion governance, data quality standards, and data-domain coordination across MACBIS source systems and CMS data owners. The position requires close collaboration with government data owners, program leadership, architects, product leaders, engineering teams, analytics and AI/ML teams, cybersecurity personnel, and source-system stakeholders to ensure program data is discoverable, trusted, governed, secure, interoperable, high quality, and fit for mission use. The ideal candidate is a strategic, hands-on data leader with deep expertise in enterprise data strategy, data governance, data management, metadata management, data quality, data integration, data lineage, data catalogs, data stewardship, data-sharing practices, and cross-organization data coordination.

Requirements

Minimum 5+ years experience serving as a Principal Data Lead, Chief Data Officer, Chief Data Architect, Data Strategy Lead, Enterprise Data Architect, Data Governance Lead, or comparable senior data leadership role on a federal IT services program.
Deep expertise in enterprise data strategy, data management, data governance, data stewardship, metadata management, data quality, data lineage, data catalogs, data classification, data interoperability, and data-sharing practices.
Demonstrated experience establishing and operating data governance frameworks across multiple data domains, source systems, work streams, vendors, or stakeholder organizations.
Experience leading data supply chain design and execution, including secure data ingestion, transformation, storage, cataloging, metadata management, quality validation, access, distribution, monitoring, and data lifecycle management.
Experience defining and implementing trusted-data promotion or certification processes for data sets, data products, analytics assets, dashboards, or shared information resources.
Experience establishing data-quality standards, data-quality rules, quality scorecards, issue-management processes, remediation workflows, and data-quality improvement programs.
Experience coordinating with data owners, data stewards, source-system teams, business stakeholders, technical delivery teams, security and privacy stakeholders, and external partner organizations.
Strong understanding of modern data architectures and platforms, including data lakes, data warehouses, lakehouses, data meshes, ETL/ELT, APIs, event-driven data integration, master and reference data, data virtualization, analytics platforms, and secure data-sharing patterns.
Experience with data-governance and data-management tools such as Collibra, Alation, Informatica, Microsoft Purview, AWS Glue Data Catalog, Apache Atlas, Databricks, Snowflake, data-quality tools, data lineage tools, or comparable technologies.
Working knowledge of cloud platforms, DevSecOps, cybersecurity, privacy, identity and access management, data encryption, auditing, monitoring, and operational controls as they relate to enterprise data services.
Experience supporting analytics, business intelligence, reporting, data science, AI/ML, or AI-enabled services and understanding the data governance and data quality considerations necessary for those capabilities.
Strong analytical, problem-solving, facilitation, conflict-resolution, communication, and stakeholder-management skills.
Ability to work independently in a remote environment while effectively coordinating data decisions and activities across distributed teams.
Eligibility to obtain a government PIV credential is required.
Ability to successfully complete a federal background investigation and receive a federal suitability determination is required.
Ability to obtain and maintain required client access credentials and any applicable clearance is required.
Ability to satisfy E-Verify employment eligibility verification requirements is required.

Nice To Haves

Prior experience supporting government client programs in a comparable mission or technical domain is preferred.
Experience supporting federal modernization, cloud migration, enterprise data, digital services, cybersecurity, systems integration, healthcare data, or large-scale technology transformation programs is preferred.
Experience with CMS data environments, MACBIS-related source systems, federally facilitated data-sharing environments, or comparable government health and human services data ecosystems is preferred.
Experience governing data used in AI/ML platforms and services, including data preparation, feature management, model inputs, retrieval-augmented generation, vector search, and responsible AI practices, is preferred.
Experience with AWS, Microsoft Azure, Google Cloud Platform, or multiple major cloud service providers is preferred.
MBA or Master's Degree in a relevant field of study is preferred.
Relevant data-management, data-governance, cloud, analytics, and architecture certifications are preferred.

Responsibilities

Lead execution of the program's data strategy in alignment with government mission priorities, enterprise data objectives, architecture, security and privacy requirements, analytics needs, AI-enabled services, and operational requirements.
Establish, operate, and continuously improve the program's data supply chain approach, including data sourcing, ingestion, transformation, validation, storage, access, distribution, consumption, monitoring, and retirement.
Lead metadata maturity activities, including the development and maintenance of business, technical, operational, and governance metadata; data catalogs; data dictionaries; data classifications; lineage; ownership; stewardship; and data-product documentation.
Establish and oversee trusted-data promotion governance to ensure data sets, data products, analytics assets, and shared information are assessed, approved, documented, monitored, and made available according to defined quality, security, privacy, stewardship, and usability standards.
Define, document, communicate, and govern data quality standards, data-quality rules, quality measurements, issue-management processes, remediation practices, and continuous-improvement activities.
Partner with MACBIS source-system stakeholders and CMS data owners to coordinate data-domain priorities, ownership, stewardship, access, quality, metadata, interoperability, and data-sharing decisions.
Facilitate data-governance forums, data-domain working groups, stewardship meetings, and decision-making processes involving government data owners, source-system teams, technical teams, and program leadership.
Define and maintain data-domain models, data ownership structures, stewardship roles, critical data elements, business glossaries, data dictionaries, and data-management policies and procedures.
Ensure data solutions support secure, appropriate, and auditable access; data privacy; data protection; data retention; data classification; data-use controls; and applicable government requirements.
Collaborate with architects, engineers, cloud teams, cybersecurity professionals, product leaders, analytics teams, AI/ML teams, and operations personnel to implement approved data standards, governance controls, integration patterns, and data-management practices.
Oversee data lineage, provenance, traceability, and auditability practices to support confidence in data used for operational, reporting, analytics, and AI-enabled use cases.
Identify, assess, document, and manage data risks, data dependencies, data-quality issues, metadata gaps, integration challenges, governance gaps, and cross-domain decision points.
Develop and maintain data strategy and governance artifacts, including data roadmaps, data-domain models, data catalogs, metadata standards, stewardship models, data-quality scorecards, lineage documentation, data-flow diagrams, data-sharing agreements, and governance decision records.
Establish and monitor data performance and maturity measures, including data quality, completeness, timeliness, accuracy, consistency, validity, uniqueness, lineage coverage, metadata completeness, access turnaround, issue remediation, and trusted-data adoption.
Support product roadmaps, release planning, Program Increment Planning, and cross-team prioritization by identifying data dependencies, readiness criteria, governance requirements, and sequencing considerations.
Provide leadership and escalation support for complex data-domain issues, data ownership conflicts, source-system constraints, data-quality concerns, and data-sharing challenges.
Evaluate data platform capabilities, data-management tools, governance approaches, data integration methods, and emerging technologies to improve mission outcomes, data trust, interoperability, analytics readiness, AI readiness, operational efficiency, and program sustainability.
Communicate data strategy, governance decisions, data-quality trends, risks, data readiness, and recommendations clearly to government and program leadership.
Perform other duties as assigned in support of program priorities and client needs.