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We are looking for a skilled AWS Data Engineer to build and support cloud-based data pipelines and analytics platforms on AWS. The role focuses on hands-on development, optimization, and operational support of data processing systems.
Job Responsibility:
Develop and maintain scalable batch data pipelines on AWS
Implement ETL/ELT jobs using AWS Glue and Spark on EMR
Build and manage workflow orchestration using Apache Airflow (MWAA)
Develop serverless data processing functions using AWS Lambda
Work with Amazon Redshift for data warehousing and analytics
Implement data storage and retrieval using Amazon DynamoDB
Use AWS DataZone for data discovery, governance, and access control
Monitor data pipelines and system health using Amazon CloudWatch
Troubleshoot data processing failures and performance issues
Collaborate with analytics, reporting, and business teams
Follow best practices for security, scalability, and cost optimization
Requirements:
5–8 years of experience in data engineering or related roles
Hands-on experience with AWS Glue
Hands-on experience with Amazon EMR
Hands-on experience with AWS Lambda
Hands-on experience with Apache Airflow (MWAA)
Hands-on experience with Amazon EC2
Hands-on experience with Amazon CloudWatch
Hands-on experience with Amazon Redshift
Hands-on experience with Amazon DynamoDB
Hands-on experience with AWS DataZone
Strong SQL and Python skills
Experience with batch data processing and data pipeline development
Understanding of data warehousing and ETL concepts
Experience working in Agile delivery environments
Nice to have:
AWS Certification
Exposure to data governance and metadata tools
Experience with performance tuning and cost optimization on AWS
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