People Data Engineer (37613013)

Job Description

Job Description

Description:
\t*This is a hybrid role, and candidates should be local to the area or located nearby*
\tROLE PURPOSEBuild the trusted data and AI foundation that powers people analytics, workforce insights, and responsible AI-enabled solutions.
\tThe People Data & AI Engineer builds and operates the trusted data and AI foundation that powers people analytics, workforce insights, and emerging AI-enabled solutions. This role designs scalable people-data architecture, integrates data across HR and enterprise platforms, establishes proactive quality and lineage controls, and ensures the reliability and governance of the People Data platform.
\tWorking within the People Analytics team and in close partnership with the Enterprise Data Team, HR Technology, Security, and People functional teams, this role translates prioritized business and product requirements into secure, governed, and production-ready data solutions.
\tIn this role, you will lead:
\tPeople Data Architecture and Engineering
\tDesign, build, and maintain scalable people-data models within the enterprise data warehouse.
\tDevelop and support data pipelines, APIs, interfaces, and integrations connecting Workday and other People systems with the enterprise data platform.
\tTranslate approved business definitions and product requirements into technical data specifications, structures, and reusable data assets.
\tEstablish architecture patterns that enable consistent use of people data across dashboards, analytics products, scorecards, and approved AI use cases.
\tPartner with the Enterprise Data Team on source-data onboarding, engineering dependencies, release planning, and production implementation.
\tMaintain technical documentation for data models, integrations, transformation logic, dependencies, and platform components.
\tData Quality, Lineage, and Reliability
\tEstablish automated data-quality monitoring, validation rules, reconciliation controls, and exception alerts for critical people-data elements.
\tImplement and maintain end-to-end data lineage, including source, transformation, calculation, and downstream consumption.
\tDefine production support, incident management, and escalation practices for people-data products.
\tMonitor platform health, pipeline performance, refresh reliability, and recurring failure patterns.
\tReduce reliance on manual, person-dependent data checks through repeatable and observable controls.
\tData Governance, Privacy, and Access
\tImplement technical controls that support approved access, privacy, confidentiality, retention, and sensitive-data handling standards.
\tPartner with People Analytics leadership, Privacy, Legal, Security, HR Technology, and the Enterprise Data Team to operationalize people-data governance requirements.
\tContribute technical definitions, source mappings, transformation logic, and lineage information to the people-data dictionary.
\tEnsure changes to sensitive people-data structures are appropriately reviewed, tested, documented, and released.
\tSkills:
\t5+ 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.
\tExperience with HR data, Workday, enterprise data warehouses, sensitive-data governance, or AI/ML data enablement is strongly preferred.
\tTechnical capabilities: SQL, Python, data modeling, ETL/ELT, APIs, cloud data platforms, version control, automated testing.
\tPlatform preferences: Experience with Workday data, Databricks or a comparable cloud data ecosystem, and BI semantic models.
\tEducation:
\tEducation/equivalent experience: Bachelor's degree in computer science, data engineering, information systems, or a related field—or equivalent practical experience.