Data Engineer (AWS+Pyspark)

Job description

**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.