AWS Data Engineer

· Build and maintain ETL pipelines using Python and Py Spark on AWS Glue and other compute platforms

· Orchestrate workflows with AWS Step Functions and serverless components (Lambda)

· Implement messaging and event-driven patterns using AWS SNS and SQS

· Design and optimize data storage and querying in Amazon Redshift

· Write performant SQL for data transformations, validation, and reporting

· Ensure data quality, monitoring, error handling and operational support for pipelines

· Collaborate with data consumers, engineers, and stakeholders to translate requirements into solutions

· Contribute to CI/CD, infrastructure-as-code, and documentation for reproducible deployments

Required Skills

· Strong experience with Python and Pyspark for large-scale data processing

· Proven hands-on experience with AWS services:
Lambda, SNS, SQS, Glue, Redshift, Step Functions

· Solid SQLSQL skills and familiarity with data modeling and query optimization

· Experience with ETL best practices, data quality checks, and monitoring/alerting

· Familiarity with version control (Git) and basic Dev Ops/CI-CD workflows