AWS Data Engineer (Pyspark)_Indore,Pune,Hyderabad,,_6 to 9 yrs
Summary
Design and optimize scalable AWS ETL pipelines using PySpark, orchestrate workflows with Glue/MWAA/Step Functions, and manage infrastructure via Terraform and Docker/EKS.
Key Responsibilities
ETL & Pipeline Development: Design and optimize scalable ETL batch pipelines in AWS for high performance and reliability.
Orchestration: Manage data workflows using tools like AWS Glue, MWAA, or Step Functions.
Data Processing: Develop large-scale processing jobs using PySpark while ensuring data quality and integrity.
Infrastructure as Code (IaC): Automate and manage AWS infrastructure using Terraform.
Containerization: Deploy and manage applications using Amazon EKS and Docker.
Required Skills & Qualifications
AWS Services: Hands-on expertise with Glue, S3, IAM, KMS, SNS, Athena, Lambda, SQS, CloudWatch, and EC2.
Programming: Proficiency in PySpark for complex data transformations.
Migration: Proven experience moving data from on-premises systems to AWS.
DevOps Tools: Skilled in Terraform for IaC and Docker/Containers for application packaging.