AWS Data Engineer

Strong hands-on AWS Data Engineering experience across large-scale cloud data platforms. • Expertise in AWS S3, AWS Glue, AWS Lambda, AWS Redshift, AWS Lake Formation, AWS CloudWatch and AWS IAM. • Strong experience in real-time and streaming data processing using Amazon Kinesis Data Streams, Kinesis Firehose, Kinesis Analytics, Amazon Kafka or equivalent streaming technologies. • Hands-on coding proficiency in Python, PySpark and SQL with strong optimization skills. • Experience building high-volume, low-latency data ingestion and transformation pipelines. • Strong experience in Databricks, Delta Lake, Structured Streaming and Spark Performance Tuning. • Experience handling TB/PB-scale datasets, partitioning strategies, file optimization, schema evolution and data lifecycle management. • Strong understanding of Data Lake, Lakehouse and Modern Data Platform architectures. • Practical data modeling experience for analytical, operational and reporting workloads. • Experience implementing CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, GitHub Actions or Jenkins. • Strong troubleshooting skills for production issues, performance bottlenecks and cost optimization. • Excellent client communication, stakeholder management and problem-solving skills.