Data Domain Architect, Senior Associate Workforce CoE
On-site · Jersey City, New Jersey, United States
Job Summary
Data Domain Architect, Senior Associate within the Workforce CoE responsible for architecting the Workforce data domain end-to-end, spanning HC, organizational structures, workforce movements, labor/benefits, and related expense measures. Hands-on depth in Databricks and SQL with domain-architecture capabilities to define canonical models, conformed dimensions, and governance-by-design. Partner with Tech, Data, Finance, and Product to standardize definitions, establish data contracts, and deliver governed data products and reports with measurable data quality, SLAs, and transparent lineage. Responsibilities include designing logical/physical data models, leading ingestion/transformation patterns, enforcing data contracts, implementing metadata standards and lineage, and enabling governed self-service for dashboards and regulatory reporting. Preferred focus includes workforce/HR datasets, lakehouse patterns, enterprise metadata/cataloging, and semantic layer support.
Required Qualifications
- Demonstrated experience in data domain architecture or closely related roles (data architecture, analytics engineering, domain data leadership) with a track record of delivering governed, reusable data assets as products
- Strong hands-on capability in SQL for complex querying, profiling, reconciliation, and performance-aware design
- Proficiency with Databricks in a lakehouse context, including designing curated datasets, working with Delta/managed tables, and applying domain modeling patterns
- Strong understanding of financial data structures and hierarchies that will need to be modeled in Databricks, and ability to communicate well (written and verbal) with Finance stakeholders
- Strong competency in logical and physical data modeling, including dimensional modeling concepts (facts/dimensions), canonical models, and the use of conformed dimensions to drive cross-domain consistency
- Practical experience implementing governance artifacts and operational controls, including metadata management, data lineage, stewardship engagement, auditability, and documented SLAs
- Strong stakeholder management skills with the ability to translate business requirements into precise data definitions, drive alignment across Product/Finance/Technology, and communicate trade-offs clearly
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