Data Engineer / Analytics Engineer – People Analytics

Why Join Omnicell?

At Omnicell, we’re transforming how healthcare organizations operate—starting with our people. 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.

What You’ll Do

Purpose: Build and maintain the core data foundation that enables secure, governed, and scalable People analytics across Omnicell.

As a Data Engineer / Analytics Engineer, You Will:

Data Engineering & Ingestion

• 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

Analytics Engineering & Data Modeling

• 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

Power BI Enablement (Scoped)

• 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

Collaboration & Governance

• 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

Who You Are

Minimum Qualifications

• 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

Preferred Qualifications

• 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

How You’ll Elevate At Omnicell

At Omnicell, success isn’t just about what you build—it’s about how you build it. Our Elevate Behaviors define how we work and grow together.

As a Data Engineer / Analytics Engineer, You Will:

• Collaborate by partnering with People Analytics, HRIS, IT, and Reporting Analysts to deliver reusable, trusted data assets
• Inspire confidence in People data by engineering reliable pipelines and consistent metrics that leaders can trust
• Develop by continuously improving data models, platform patterns, and documentation that scale beyond individual ownership
• Execute with discipline—monitoring pipelines, resolving issues quickly, and delivering durable solutions
• Impact the organization by enabling governed analytics today and laying the groundwork for AI‑enabled insights tomorrow

Role Scope & Guardrails

This Role Is not Responsible For:

• Data science or machine learning model development
• Predictive analytics ownership
• Ongoing ad‑hoc dashboard requests or executive storytelling
• Pixel‑level Power BI report design

Focus: Build once. Reuse everywhere. Engineer for trust today—enable intelligence tomorrow.