Data Engineer (AWS+Pyspark)

Job description

DRequired Skills JOB DESCRIPTION • 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.