Key Responsibilities
• Develop and maintain data pipelines using PySpark and AWS Glue.
• Build serverless data processing solutions using AWS Lambda.
• Design and optimize data storage and analytics solutions on S3, Athena, Redshift, and DynamoDB.
• Implement ETL/ELT processes for data ingestion and transformation.
• Ensure data quality, performance, and reliability across data platforms.
• Collaborate with cross-functional teams to understand and deliver business requirements.
• Monitor, troubleshoot, and support production data workflows. Required Skills
• Strong experience with Python and PySpark.
• Strong expertise of optimizations
• Hands-on experience with AWS Glue, Lambda, S3, Athena, Redshift, and DynamoDB.
• Solid SQL and data analysis skills.
• Experience building and optimizing large-scale data pipelines.
• Good understanding of data warehousing and data lake concepts. Good to Have
• Experience with Git and CI/CD pipelines.
• Knowledge of Infrastructure as Code (Terraform or CloudFormation).
• Experience with data quality and data governance frameworks.
• AWS certifications.
• Exposure to real-time or event-driven data processing solutions.

📌 AWS Data Engineer (Hyderabad)
🏢 Paltech
📍 Hyderabad