HR Data Engineer

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Requirements:

• 5+ years of experience in HR Data Engineer role leading HR data engineering transformation and implementing data pipelines and data solutions in the People Analytics/HR domain
• Very good understanding of HR data and HR employee lifecycle processes (talent acquisition, talent development, workforce planning, engagement, employee listening, external benchmarking etc.)
• Very good understanding of HCM data architecture, models and data pipelines and experience designing and implementing data integrations and ETLs with Workday (RaaS, APIs)
• Experience designing and automating data and analytics solutions that can provide insights and recommendations at scale
• Proficiency in SQL, R/Python and ETL tools
• Deep expertise in modern data platforms (particularly Databricks) and end-to-end data architecture (DLT Streaming Pipelines, Workflows, Notebooks, DeltaLake, Unity Catalog)
• Experience with different authentication (Basic Auth, Oauth, etc.) and encryption methods and tools (GPG, Voltage, etc.)
• Very strong data analytics skills and ability to leverage multiple internal and external data sources to enable data-driven insights and inform strategic talent decisions
• Knowledge of compliance and regulatory requirements associated with data management
• Experience working in environments requiring strict confidentiality and handling of sensitive data
• Great communication skills and ability to explain complex technical concepts to non-technical stakeholders.
• Degree with quantitative focus (e.g., Mathematics, Statistics) and/or degree in Human Resources is a plus

Responsibilities:

• Design, develop, and maintain ETL/ELT processes for HR data from multiple systems including Workday to empower data-driven decision-making
• Drive implementation of robust HR data models and pipelines optimized for reporting and analytics, ensuring data quality, reliability, and security for on-prem and Azure cloud solutions.
• Develop pipelines and testing automation to ensure HR data quality and integrity across multiple data sources
• Collaborate with People Analytics and HR business partners to understand data requirements and deliver reliable solutions. Collaborate with technical teams to build the best-in-class data environment and technology stack for People Analytics teams.
• Ensure data integrity, quality, consistency, security, and compliance (e.g., GDPR, CCPA, HIPAA where applicable).
• Design and implement secure processes for handling sensitive information in our data tech stack while maintaining appropriate access controls and confidentiality
• Automate manual HR reporting and improve data accessibility through scalable data pipelines across the entire HR employee lifecycle
• Troubleshoot and resolve data-related issues quickly and efficiently.
• Contribute to HR tech stack evaluations and migrations, especially around data capabilities and API integrations.
• Incorporate external data sources into internal datasets for comprehensive analysis
• Manage and optimize platform architecture including Databricks environment configuration and performance optimization
• Stay up to date with emerging trends and advancements in data engineering – both technically and in the HR and People Analytics/sciences domain