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
Robust experience with Python and PySpark.
Strong expertise of optimizations
Hands-on experience with AWS Glue, Lambda, S3, Athena, Redshift, and DynamoDB.
Strong SQL and data analysis skills.
Experience building and optimizing large-scale data pipelines.
Valuable understanding of data warehousing and data lake concepts.

Positive 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