Data Engineer (DataBricks)

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and Python
• Build and optimize ETL/ELT processes for large-scale data ingestion and transformation
• Develop and maintain data models, data marts, and enterprise Data Warehouse (DWH) solutions
• Write efficient, complex SQL queries for data extraction, transformation, and reporting
• Ensure data quality, integrity, and consistency across multiple source systems
• Implement performance tuning and optimization strategies for Databricks workloads
• Follow DevOps best practices for CI/CD, version control, and automated deployment processes
• Collaborate closely with cross-functional teams to troubleshoot and resolve data-related issues

Required Skill

sPrimary Skillse

• tAtleast 3- 5 years in working with Databrick
• sProficiency in Python and PySpar
• kAdvanced knowledge of SQ
• LStrong experience in Data Warehousing (DWH) concepts and implementatio
• nExperience designing and optimizing ETL/ELT pipeline
• sKnowledge of data modeling techniques (Star Schema, Snowflake Schema, Dimensional Modeling
• )Experience handling large datasets, with a focus on performance optimizatio
• nExperience with DevOps tools and practices (CI/CD pipelines, Git, Azure DevOps, Jenkins, etc.
• )Understanding of cloud-based data platforms (Azure, AWS, or GCP
• )Deep understanding of IPPL (Integrated Planning Product Line

)
Good to Ha

• veExposure to SAP BDC (Batch Data Communication) processes and SAP data integration concep
• tsExperience integrating SAP and non-SAP syste
• msKnowledge of Delta Lake, Unity Catalog, and Databricks Lakehouse architectu