Job Description & Details
This is a specialized data engineering role focused on building the foundational architecture for workforce analytics and AI-enabled HR solutions at a Fortune 500 company. Instead of just maintaining old reporting pipelines, you'll be designing scalable data models and handling complex Workday integrations that directly influence executive decision-making.
What You'll Actually Be Doing
Your day-to-day will revolve around designing and maintaining robust data models in the enterprise warehouse, building out the integration layer between Workday and the broader data ecosystem, and establishing rigorous data quality monitoring. You'll spend a significant amount of time collaborating with Legal, Privacy, Security, and HR Technology teams to operationalize strict data governance policies, ensuring sensitive employee data is handled correctly and transparently.
The Core Tech Stack
You need to bring a strong command of SQL and Python, coupled with hands-on experience designing production-grade ETL/ELT pipelines and API integrations. Cloud data platforms, version control, and automated testing are non-negotiable here because leadership needs absolute trust in the data lineage. If you have background specifically with Workday data, Databricks, or BI semantic modeling, you'll find yourself right at home.
Interview Expectations
Expect the hiring team to test your deep understanding of data modeling principles and your ability to design resilient pipelines that handle sensitive, highly restricted data safely. You'll likely be asked how you would architect a secure integration layer between an HRIS like Workday and a cloud warehouse while maintaining end-to-end data lineage and automated quality checks. They aren't just looking for code that works; they want to see that you understand how to build systems that non-technical stakeholders and legal teams can completely trust.
Application Advice
To get past the ATS and grab the recruiter's attention, make sure your resume explicitly highlights your experience with complex data modeling, pipeline automation, and API integrations rather than just basic reporting. Weave in keywords from the job description like Workday, ETL/ELT, data lineage, and cloud data platforms, and use a conversational narrative to show that you care as much about data governance and security as you do about writing clean Python and SQL.