Data Full Stack Engineer (Workday ERP & Databricks)
Overview:Data Full Stack Engineer (Workday ERP & Databricks)Job SummaryWe are seeking a Data Full Stack Engineer with strong expertise in Workday ERP (Finance & HCM) and modern data engineering platforms (Databricks).The ideal candidate will own the end-to-end data lifecycle, including extraction of Workday data, building scalable pipelines, and delivering analytics-ready datasets for Finance and HR use cases.This role bridges ERP domain knowledge and data engineering, enabling reliable and governed data solutions in a Lakehouse architecture.Key ResponsibilitiesWorkday Integration & Data ExtractionDesign and develop integrations to extract data from:Workday Financial modules (GL, AP, AR, Invoicing, Supplier/Customer data)Workday HCM modules (Workers, Compensation, Absence, Recruiting)Build and maintain:RaaS (Reports-as-a-Service)WQL (Workday Query Language) reportsDevelop integrations using:REST / SOAP APIsManage:Integration System Users (ISUs)Security roles and access controlsData Engineering (Databricks)Build scalable ETL/ELT pipelines using:PySparkSpark SQLDelta LakeDesign and implement:Lakehouse architecture (Bronze / Silver / Gold layers)Optimize pipelines for:PerformanceReliabilityCost efficiencyData Modeling & TransformationDevelop enterprise-scale data modelsTransform Workday data into:Analytics-ready datasetsEnsure data quality and consistencyData Governance & SecurityImplement:Data quality checksValidation frameworksMonitoring and alertingManage:Access controlData lineageCompliance requirementsBusiness & Analytics EnablementCollaborate with:Finance, HR, and Analytics teamsDeliver:Reporting datasetsDashboards (Power BI / Tableau)Support:Business insights and decision-makingCollaboration & Agile DeliveryWork in Agile/Scrum environmentsPartner with:Workday consultantsData engineersBusiness stakeholders• Required SkillsWorkday Expertise (MANDATORY)Workday Financial Management (GL, AP, AR, etc.)Workday Reporting (RaaS, WQL)Workday integrations (REST/SOAP APIs)Data EngineeringDatabricks (Azure preferred)PySpark, Spark SQL, Delta LakeETL/ELT pipeline developmentProgramming & DatabasesPythonSQL (Advanced)Data modelingCloudAzure (preferred) / AWS / GCPAdditional SkillsData governance & securityCI/CD pipelinesAPI integrationExperience Required5-10 years of experienceMinimum:3+ years in Workday3+ years in Databricks / data engineeringGood to HavePower BI / TableauUnity Catalog (Databricks governance)Experience with Finance & HR analyticsKnowledge of AI/ML data pipelines