Data Engineer / Analytics Engineer - People Analytics
Role details
Job location
Tech stack
Job description
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., Purpose: Build and maintain the core data foundation that enables secure, governed, and scalable People analytics across Omnicell., * 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, * 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
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