Data Engineer / Analytics Engineer – People Analytics

Omnicell is transforming healthcare operations with a focus on People Analytics. The Data Engineer / Analytics Engineer will design and build the People Data Hub, ensuring secure and scalable analytics while collaborating with various teams to deliver reliable data assets.

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