Data Engineer (AWS+Pyspark)

DRequired Skills
4–7 years of hands-on experience as a Data Engineer, designing, building, and supporting data pipelines on AWS.
Strong programming skills in Python and PySpark, with hands-on experience in distributed data processing and big data frameworks.
Strong SQL expertise, including complex query writing, performance optimization, and working with large datasets across relational and analytical databases.
Proven experience working with AWS core services, including Lambda, RDS, CloudWatch, CloudTrail, SNS, and SQS.
Hands-on experience with AWS data and analytics services such as:
IAM, EMR, AWS Glue, Lambda, Lake Formation, RDS, DynamoDB, and related services.
Strong expertise in IAM management, including role design, policy creation, permission boundaries, and enforcing least-privilege access.
Experience in building and maintaining end-to-end data ingestion, transformation, and processing pipelines.
Solid understanding of monitoring, logging, and alerting, leveraging CloudWatch and CloudTrail.
Excellent debugging, troubleshooting, and root cause analysis skills across data pipelines and AWS services.