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Data Full Stack Engineer – Workday ERP & Databricks

Job in Troy, Oakland County, Michigan, 48083, USA
Listing for: Hirextra -World's First Staffing Aggregator
Full Time position
Listed on 2026-06-06
Job specializations:
  • Software Development
    Data Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
  • Design, develop, and maintain data integration solutions between Workday HCM/Finance and enterprise systems.
  • Build scalable data pipelines using Databricks
    , Py Spark ,
    Spark SQL
    , and Delta Lake
    .
  • Develop and optimize Workday reports, calculated fields, and data extraction processes using Workday Reporting
    , RaaS (Reports as a Service), and WQL (Workday Query Language).
  • Create and maintain APIs and integrations using REST and SOAP web services.
  • Develop ETL/ELT processes to ingest, transform, and load Workday data into enterprise data platforms.
  • Collaborate with HR, Finance, and business stakeholders to gather requirements and deliver data solutions.
  • Ensure data quality, governance, security, and compliance across Workday integrations.
  • Troubleshoot performance issues and optimize data processing workflows.
  • Support production deployments, enhancements, and ongoing maintenance activities.
Required Skills
  • Strong experience with Workday HCM and/or Workday Finance
    .
  • Hands‑on experience with RaaS
    , WQL
    , and Workday Reporting
    .
  • Expertise in Databricks
    , Py Spark ,
    Spark SQL
    , and Delta Lake
    .
  • Strong proficiency in Python and SQL
    .
  • Experience developing integrations using REST APIs and SOAP Web Services
    .
  • Knowledge of ETL/ELT design patterns and large‑scale data processing.
  • Experience with cloud‑based data platforms and modern data architectures.
  • Strong analytical, troubleshooting, and problem‑solving skills.
Preferred Skills
  • Workday integration tools such as EIB, Studio, and Cloud Connect.
  • Experience with Azure, AWS, or GCP data platforms.
  • Knowledge of CI/CD pipelines and Dev Ops practices.
  • Understanding of data warehousing and dimensional modeling concepts.
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