People Data Engineer

Hybrid Data Engineering RoleThis is a hybrid role, and candidates should be local to the area or located nearby.Design, build, and maintain scalable people-data models within the enterprise data warehouse.Develop and support data pipelines, APIs, interfaces, and integrations connecting Workday and other People systems with the enterprise data platform.Translate approved business definitions and product requirements into technical data specifications, structures, and reusable data assets.Establish architecture patterns that enable consistent use of people data across dashboards, analytics products, scorecards, and approved AI use cases.Partner with the Enterprise Data Team on source-data onboarding, engineering dependencies, release planning, and production implementation.Maintain technical documentation for data models, integrations, transformation logic, dependencies, and platform components.Establish automated data-quality monitoring, validation rules, reconciliation controls, and exception alerts for critical people-data elements.Implement and maintain end-to-end data lineage, including source, transformation, calculation, and downstream consumption.Define production support, incident management, and escalation practices for people-data products.Monitor platform health, pipeline performance, refresh reliability, and recurring failure patterns.Reduce reliance on manual, person-dependent data checks through repeatable and observable controls.Implement technical controls that support approved access, privacy, confidentiality, retention, and sensitive-data handling standards.Partner with People Analytics leadership, Privacy, Legal, Security, HR Technology, and the Enterprise Data Team to operationalize people-data governance requirements.Contribute technical definitions, source mappings, transformation logic, and lineage information to the people-data dictionary.Ensure changes to sensitive people-data structures are appropriately reviewed, tested, documented, and released.Minimum of 5 years of progressive experience in data engineering, analytics engineering, data architecture, or a related field, including experience building production-grade data pipelines, models, integrations, and quality controls.Experience with HR data, Workday, enterprise data warehouses, sensitive-data governance, or AI/ML data enablement is strongly preferred.Technical capabilities: SQL, Python, data modeling, ETL/ELT, APIs, cloud data platforms, version control, automated testing.Platform preferences: Experience with Workday data, Databricks or a comparable cloud data ecosystem, and BI semantic models.