AWS Data Engineer

Key Responsibilities

• Design and implement scalable ETL/ELT data pipelines using

  AWS Glue

  ,

  PySpark

  , and

  Python

  .
• Develop data workflows integrating multiple AWS services such as

  S3

  ,

  Lambda

  ,

  EMR

  ,

  Athena

  ,

  Redshift

  ,

  SNS

  , and

  SQS

  .
• Optimize data storage and retrieval performance on AWS.
  
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver data-driven solutions.
  
• Implement best practices for data governance, quality, and security within AWS environments.
  
• Monitor, troubleshoot, and improve data pipeline performance and reliability.
  

Technical Skills Required

• Strong hands-on experience with

  AWS Services

  : Glue, Lambda, S3, EMR, Athena, Redshift, SNS, SQS, etc.
• Proficiency in

  PySpark

  and

  Python

  programming.
• Solid understanding of data warehousing, data modeling, and ETL concepts.
  
• Experience with version control tools (e.g., Git) and CI/CD practices.
  
• Familiarity with data lake architecture and modern data platform concepts.
  

Preferred Qualifications

• AWS Certification (e.g., AWS Data Analytics Specialty or AWS Solutions Architect) is a plus.
  
• Experience working in Agile or DevOps-based environments.
  
• Strong problem-solving and analytical skills with attention to detail.