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Job Description & How to Apply Below
Hybrid work mode
Hyderabad
6+ Years
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python and PySpark .
Build and optimize ETL/ELT workflows using AWS Glue .
Develop serverless data processing solutions using AWS Lambda .
Design and manage data lakes using Amazon S3 .
Build and optimize data warehouse solutions using Amazon Redshift .
Write complex and optimized queries using SQL .
Implement and manage table formats using Apache Iceberg .
Ensure data quality, integrity, governance, and performance tuning.
Collaborate with data analysts, data scientists, and cross-functional teams.
Implement CI/CD pipelines and automation for data workflows.
Monitor, troubleshoot, and optimize data jobs and pipelines.
Required Skills
Strong hands-on experience with AWS (Glue, Redshift, Lambda, S3) .
Proficiency in Python and PySpark .
Strong command of SQL (query optimization, performance tuning).
Experience implementing Apache Iceberg in data lake environments.
Experience building scalable ETL/ELT pipelines.
Knowledge of data modeling and warehouse design.
Understanding of distributed data processing concepts.
Preferred Skills
Experience with data lake architecture and lakehouse concepts.
Knowledge of partitioning strategies and performance tuning in Iceberg.
Familiarity with Dev Ops practices and CI/CD pipelines.
Experience with data governance and security best practices in AWS.
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