Data Full Stack Engineer – Workday ERP & Databricks at Troy, MI

Role: Workday ERP & Databricks Engineer
Location : Troy, MI (Onsite)
Duration: 12 Months

Data Full Stack Engineer – Workday ERP & Databricks (Focused JD)

Must Have Experience
• Strong hands-on experience with Workday Financial Management modules including General Ledger, Accounts Payable, Accounts Receivable, Customer Invoicing, Supplier and Customer Master data
• Proven experience with Workday Reporting including RaaS (Reports-as-a-Service), custom reports, calculated fields and WQL for downstream data consumption
• Solid Workday integration experience using REST and SOAP APIs, including handling security, authentication and incremental data extracts
• 3+ years of experience building and optimizing data pipelines on Databricks using PySpark, Spark SQL and Delta Lake
• Strong SQL and Python skills with experience in enterprise-scale data modeling
• Experience working on cloud platforms, preferably Azure

Key Responsibilities
• Lead extraction of Workday Finance and HCM data with primary focus on Finance reporting and analytics use cases
• Design, develop and maintain Workday reports and APIs to support reliable data integrations
• Build and manage scalable ETL/ELT pipelines in Databricks, following Bronze, Silver and Gold Lakehouse patterns
• Manage Workday integration setup including Integration System Users, security domains and access controls
• Implement data quality checks, monitoring and error handling for production data pipelines
• Collaborate closely with Finance, HR and Analytics teams to deliver trusted, analytics-ready datasets

Required Skills
• Deep understanding of Workday Finance data structures and reporting concepts
• Hands-on expertise in Workday Reporting, RaaS, WQL and integration services
• Strong Databricks skills including PySpark, Spark SQL and Delta Lake
• Data integration and ETL best practices in cloud environments
• Advanced SQL, Python and data modeling skills
• Understanding of data governance, security and access management

Role Descriptions: About the Role
We are looking for a seasoned Data Fullstack Engineer who combines deep functional knowledge of Workday ERP (Finance and HCM) with strong hands-on expertise in the Databricks data platform. In this role, you will own the end-to-end data lifecycle from extracting and integrating Workday data through scalable pipelines, to building analytical assets that power business decisions across Finance and HR.
This is a unique profile that bridges the gap between ERP domain knowledge and modern data engineering. You will work closely with Finance, HR, and IT stakeholders to ensure Workday data flows reliably into our Lakehouse architecture and is transformed into trusted, governed datasets ready for analytics and AI.

Workday Integration & Data Extraction
Design and build integrations to extract data from Workday Financial Management (GL, AP, AR, Customer Invoices, Customer Master, Supplier data) and HCM (Workers, Compensation, Absence, Recruiting, Talent) modules
Develop and maintain custom reports using Workday RaaS (Reports-as-a-Service), WQL (Workday Query Language), and SOAP/REST APIs
Configure and manage Integration System Users (ISUs), security groups, and OAuth 2.0 API clients within Workday
Collaborate with Workday functional consultants and administrators to identify optimal data sources, understand business object relationships, and resolve data quality issues
Implement incremental sync patterns, error handling, and monitoring for production-grade Workday integrations
Databricks & Data Platform
Build and optimize scalable ETL/ELT pipelines in Databricks using PySpark, Spark SQL, and Delta Lake
Design and implement a Lakehouse architecture (Bronze, Silver, Gold) for Workday Finance and HCM data, ensuring data quality at every layer
Develop and maintain data models that serve downstream analytics, reporting, and machine learning use cases
Leverage Databricks Unity Catalog for data governance, access control, lineage, and compliance
Optimize Databricks workloads for performance, cost efficiency, and reliability (cluster configuration, job scheduling, auto-scaling)
Implement data quality frameworks (expectations, validation rules, anomaly detection) within the pipeline
Analytics & Business Enablement
Build curated datasets and Gold-layer views for Finance (billing summaries, aging reports, revenue analytics) and HR (headcount, turnover, compensation benchmarking) use cases
Collaborate with business analysts and data scientists to understand requirements and deliver self-service data products
Create and maintain dashboards and reporting integrations (Power BI, Tableau, or similar) connected to the Databricks Lakehouse
Document data pipelines, data dictionaries, and integration specifications

What You Bring
Required
5 years of experience in data engineering, integration development, or a related data role
3 years of hands-on experience with Workday ERP including at least one of Workday Financial Management (General Ledger, Accounts Payable, Accounts Receivable, Customer Invoicing, Supplier and Customer Master data) or Workday HCM modules
Strong skills in Databricks, PySpark, Spark SQL, Delta Lake
Advanced SQL and Python programming skills
Experience with cloud platforms, preferably Azure
Understanding of data governance, security, and access management