Description

You will design and build scalable ETL pipelines using AWS Glue, Lambda, and S3.

Responsibilities

• Develop and manage cloud-based data infrastructure on AWS, focusing on scalability, reliability, and security.
• Automate workflows using Python, PySpark, and AWS services for both real-time and batch data processing.
• Optimize performance and cost for high-throughput data systems.
• Collaborate with cross-functional teams to deliver data solutions.

Required Skills

• 5+ years in Data Engineering.
• 3+ years of hands-on AWS expertise (EC2, S3, Glue, Lambda).
• Advanced proficiency in Python and PySpark.
• Experience with Big data platforms, including Spark and Hadoop.
• Knowledge of AWS data lakes and warehouses (Redshift, Athena).
• Familiarity with data pipeline architecture.

Preferred Skills

• AWS Certified Data Analytics or Solutions Architect certification.

Key Skills

Education

Any Graduate