About The Position

The People Analytics team is evolving beyond traditional dashboards to build a trusted, scalable data foundation that powers insight, compliance, and innovation across the enterprise. As a Data Engineer / Analytics Engineer – People Analytics, you’ll play a critical role in designing and building the People Data Hub that enables trusted HR reporting today and prepares Omnicell for Workday, AI‑enabled analytics, and future HR system integrations. This is a high‑impact role for an engineer who enjoys building durable data platforms, reducing operational risk, and enabling analytics at scale.

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

Nice To Haves

  • 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

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

Benefits

  • Learning and well-being programs
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