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Role Overview We’re looking for a Data Engineer who’s passionate about building scalable, high-performance data solutions that empower analytics and business decisions. In this role, you’ll design, develop, and optimize data pipelines using PySpark, Databricks, and Delta Lake , ensuring data integrity and reliability across large distributed systems. Key Responsibilities Build and maintain robust, high-performance data pipelines using PySpark , Databricks , and Delta Lake . Develop a strong understanding of data models, lineage, and business logic — not just ETL flow. Ensure data quality, consistency, and accuracy through validation, profiling, and automated testing. Debug, optimize, and fix issues across large-scale distributed systems . Collaborate with analysts and business teams to deliver trustworthy, production-ready datasets . Apply CI/CD, version control, and testing frameworks to maintain reliability and scalability. Qualifications 3–5 years of hands‑on experience in data engineering or equivalent. Strong expertise in PySpark , SQL , data modeling , and performance tuning . Proven experience in data quality frameworks , unit testing , and data validation . Hands‑on with Synapse , Databricks , Azure/AWS . Curious and analytical mindset — you understand what data represents , not just how it’s moved. Nice to Have Exposure to streaming data , CDC , or real‑time processing . Familiarity with Power BI or other BI tools. Experience in retail or supply‑chain domains is a plus. #J-18808-Ljbffr