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Data Engineer / Analytics Engineer – People Analytics
- Austin, Texas, United States
- Austin, Texas, United States
About
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.
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Languages
- English
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