Principal Data Lead

About Us

eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow.

Full-time

The Principal Data Lead will lead data strategy execution, data supply chain operations, metadata maturity, governed data asset promotion governance, data quality standards, and data-domain coordination for a large-scale federal data and analytics modernization program. The program supports governed data assets, reusable analytics, dashboards, APIs, public-facing reporting, and AI-enabled services. This role will improve source onboarding, data promotion, metadata maturity, data quality, lineage, stewardship, and data-domain coordination.

The Principal Data Lead will ensure data assets are discoverable, governed, documented, quality-controlled, and suitable for self-service analytics and responsible AI expansion.

• Lead data strategy execution, data supply chain and metadata maturity leadership, governed data asset promotion governance, data quality standards, and data-domain coordination across source systems and data owners.
• Oversee applicable coverage areas, including data platform operations, distributed processing, programming and query languages, jobs and workflows, schema design, optimization, pipeline reliability, governance layers, metadata maturity, machine-readable documentation, lineage, governed data asset promotion, analytics discoverability, and domain stakeholder engagement.
• Operate and improve source onboarding, ingestion, transformation, data quality, platform operations, compute governance, connectors, endpoints, workspace administration, and documentation for reusable data assets.
• Advance the program’s data trust model by defining and applying admission, promotion, ownership, stewardship, lineage, refresh, trust indicator, documentation, and retirement standards for governed data assets.
• Establish and monitor data quality and processing timeliness practices, including completeness, conformance, quality pass rates, defect trends, freshness against service levels, rework drivers, schema drift events, and defect remediation.
• Coordinate with data owners, source-system teams, product teams, public-facing dashboard teams, BI teams, AI teams, and approved consumers to improve data contracts, ingestion readiness, metadata standards, and downstream reuse.
• Ensure metadata maturity advances as a tracked, multi-year effort and that AI use cases do not scale beyond appropriate users until supporting metadata quality, lineage, documentation, and governance are sufficient for reliable outputs.
• Support governed self-service analytics, certified dashboards, public-facing products, secure data sharing, reusable APIs, modernization of legacy analytics workflows, and publication workflows through governed data assets, documentation, and data governance standards.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Math, or other related scientific or technical discipline. With twelve years of general information technology
• 14+ year's experience in software engineering, including implementing engineering best practices, iterative/continuous engineering principles
• All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation
• Demonstrated ability to lead enterprise data strategy, data engineering, data governance, metadata, data quality, or data platform operations in a complex analytics environment.
• Experience with…