Posted:14 hours ago|
Platform:
Work from Office
Full Time
Role & responsibilities Design and develop scalable data pipelines using PySpark , Hive , and SQL on distributed data platforms. Apply Spark optimization techniques to ensure performance and reliability in processing large volumes of data. Collaborate with cross-functional teams including data scientists, analysts, and product managers to understand data requirements and translate them into robust data solutions. Participate in code reviews, technical design discussions, and contribute to architectural decisions. Implement automated testing frameworks and CI/CD pipelines for data workflows. Ensure high data quality, integrity, and availability across platforms. Troubleshoot and resolve performance, reliability, and data quality issues in existing pipelines. Preferred candidate profile 7 years of experience in Big Data engineering and data pipeline development. Strong proficiency in PySpark , Python , SQL , and Hive . Deep understanding of Spark internals and performance optimization strategies. Experience with large-scale data processing and distributed computing. Hands-on experience with application design , software development , and automated testing . Solid understanding of data warehousing concepts and ETL/ELT best practices.
Thinqor Solutions
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