Job Description: Databricks Engineer - HR/Payroll Analytics
Experience: 8-10 Years
Location : Remote
Job Type: Full Time
Job Summary:
We are seeking an experienced Databricks Engineer with strong expertise in building scalable data platforms, data engineering solutions, and analytics applications on the Databricks Lakehouse platform. The ideal candidate should have experience working with HR/Payroll Analytics datasets, enabling enterprise reporting, advanced analytics, and business intelligence solutions.
The candidate will be responsible for designing, developing, and optimizing data pipelines, integrating enterprise applications, and delivering high-quality data products to support business decision-making.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and SQL.
- Build and optimize ETL/ELT processes for structured, semi-structured, and unstructured data.
- Develop and manage data ingestion frameworks from ERP, HRMS, Payroll systems.
- Implement Delta Lake architecture, Medallion Framework (Bronze, Silver, Gold), and Lakehouse best practices.
- Collaborate with business stakeholders to understand reporting and analytics requirements.
- Develop data models and data marts for HR, Payroll analytics.
- Ensure data quality, governance, security, and compliance standards are met.
- Optimize Databricks workloads for performance, scalability, and cost efficiency.
- Support enterprise reporting solutions using Power BI, Tableau, or other BI platforms.
- Troubleshoot and resolve data integration and performance issues.
- Participate in architecture reviews and recommend best practices for cloud data engineering.
Required Technical Skills:
- Strong experience with Databricks Lakehouse Platform
- Expert in PySpark, Spark SQL, and DataFrame APIs
- Experience with Delta Lake, Unity Catalog, and Databricks Workflows
- Hands-on experience with Azure Data Factory (ADF), Azure Synapse, or equivalent integration tools
- Strong SQL development and performance tuning skills
- Experience with cloud platforms (Azure, AWS, or GCP)
- Data modeling and warehouse concepts
- CI/CD implementation using Azure DevOps, GitHub Actions, or Jenkins
- Knowledge of data governance and security best practices
- Experience with REST APIs and file-based integrations
Preferred Skills:
- Experience integrating with SAP SuccessFactors, SAP HCM, Workday, ADP, Oracle HCM, or similar HR/Payroll systems.
- Experience with SAP ECC, SAP S/4HANA, SAP BW, or SAP Datasphere.
- Exposure to Microsoft Fabric, Power BI, and real-time analytics.
- Experience with Data Quality and Master Data Management solutions.
Qualofications:
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
- 8–10 years of experience in Databricks
- Databricks Certification is preferred.
- Relevant experience in enterprise data engineering and analytics projects.
Nice To Have:
- Databricks Certified Data Engineer Associate/Professional.
- Experience in implementing enterprise-scale Lakehouse architectures.
- Knowledge of AI/ML integration within Databricks.
