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.