Data Engineer / Analytics Engineer – People Analytics

Omnicell is transforming how healthcare organizations operate, and they are seeking a Data Engineer / Analytics Engineer for their People Analytics team. This role involves designing and building the People Data Hub to enable trusted HR reporting and support future HR system integrations while ensuring secure and scalable People analytics across the organization.

Responsibilities:

• Design, build, and maintain automated ingestion pipelines from HR and People systems using APIs, databases, and file‑based sources
• Ingest and transform data using modern platforms such as Microsoft Fabric, Databricks, and SQL‑based environments
• Monitor data pipelines and proactively resolve refresh failures, schema changes, and upstream data quality issues
• Implement reusable, scalable transformation patterns that minimize report‑level logic and improve long‑term reliability
• Build and maintain analytics‑ready data models (facts, dimensions, and semantic layers) aligned to defined standards
• Centralize metric definitions and business logic to ensure consistent, trusted reporting across the organization
• Create, manage, and optimize certified Power BI datasets for reuse by Reporting Analysts and business partners
• Optimize models for performance, scalability, and downstream analytics consumption
• Support Power BI primarily at the dataset and data‑model level, not pixel‑level report design
• Define standardized measures and KPI logic to enable governed self‑service analytics
• Build or refine foundational dashboards when needed to validate data models or support adoption
• Partner closely with the People Analytics Lead on architecture, standards, and prioritization
• Enable Reporting Analysts with clean, reliable, and well‑documented datasets
• Align data engineering work with HRIS, IT, and Workday readiness initiatives, ensuring security, privacy, and scalability

Requirements:

• Minimum 3 years of experience building and supporting production‑grade data pipelines and transformations
• Strong SQL expertise and experience working with relational and analytical data models
• Hands‑on experience with Databricks, including ingestion, transformations, notebooks, and Delta Lake concepts
• Experience working in modern data platforms such as Microsoft Fabric, data lakes, or cloud analytics environments
• Proven ability to design analytics‑ready data models (facts, dimensions, semantic layers)
• Experience supporting Power BI through dataset development, measure definition, and performance optimization
• Experience working with sensitive or regulated data (HR, financial, or similar), including role‑based access and privacy controls
• Strong documentation skills for data models, pipelines, and assumptions
• Experience working with HR, People, or workforce data domains
• Exposure to REST API‑based integrations (e.g., Workday, Oracle, or similar systems)
• Familiarity with AI‑enabled analytics concepts (e.g., natural‑language querying or Copilot‑style tools), without direct model development responsibility