Data Product Engineer
CMT Services Inc•Washington, DC
•Hybrid
About The Position
The Data Product Engineer will support the USDA’s Enterprise Human Capital Modernization & Transformation initiative. In this role, the Data Product Engineer develops and maintains dashboards, APIs, and analytical data products. Translates business requirements into scalable, secure data solutions with full lifecycle management.
Requirements
- 3 to 5 years of progressive professional experience supporting HCM data and analytics solutions.
- Experience developing and maintaining dashboards, APIs, and analytical data products supporting Human Capital data requirements.
- Experience translating business and data requirements into scalable and secure data solutions, including requirements supporting data migration, system integration, reporting, analytics, and downstream data consumption.
- Experience supporting data discovery, source-to-target mappings, transformation logic, validation criteria, and data flow/pipeline requirements associated with HCM data migration.
- Experience supporting the USDA Databricks Lakehouse as a governed repository for HCM reporting and analytics and as an integration platform for secure data exchange and interoperability with related systems.
- Experience supporting common HCM data models, including data definitions, authoritative sources, relationships, metadata, lineage, governance attributes, and alignment with reporting, integration, migration, and analytics requirements.
- Experience managing data products through their full lifecycle, including development, integration, validation, maintenance, and enhancement.
- Bachelor’s degree in computer science, Information Systems, Information Technology, Computer Engineering.
Responsibilities
- Develops and maintains dashboards, APIs, and analytical data products.
- Translates business requirements into scalable, secure data solutions with full lifecycle management.
- Data Migration Planning & Coordination: Migration strategy, plans, timelines, crosswalks, mapping rules, trial migrations, reconciliation
- Data Quality & Cleansing: Data quality assessments, dashboards, cleanup campaigns, standards compliance
- Data Governance & Metadata Management: Metadata standards, stewardship, lineage, authoritative data sources
- Systems Integration Engineering: APIs, integrations, interface design, ICDs, ETL/ELT pipelines, interface remediation, integration testing
- Business & Functional Analysis: Requirements gathering, readiness assessment, risk analysis, UAT support, business process development
- Testing & Validation: Test cases, reconciliation scripts, UAT coordination, data verification
- Databricks Lakehouse Support: Lakehouse architecture, security design, common data model, migration framework, reporting and analytics
- Knowledge Transfer: Training, SOPs, workshops, shadowing sessions, documentation, repository management
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
