The role involves designing, developing, and optimizing scalable data pipelines and cloud-native data solutions on AWS. The ideal candidate should have robust hands-on experience in Python, PySpark, AWS data services, ETL/ELT frameworks, and large-scale data processing environments.
Responsibilities
• Design and develop scalable data pipelines using Python and PySpark.
• Build and optimize ETL/ELT processes on AWS cloud platforms.
• Create and maintain Data Lake and Data Warehouse solutions.
• Develop batch and real-time data processing applications.
• Perform data quality validation, monitoring, and troubleshooting.
• Optimize Spark workloads for performance, scalability, and cost efficiency.
• Collaborate with stakeholders, architects, and development teams to deliver enterprise-scale data solutions.
• Support production deployments and critical incident resolution.
? Qualification: BE / B.Tech / MCA / M.Tech or equivalent.
? If you are interested, please share your updated CV.