Sr. AWS Data Engineer

AWS Data EngineerDesign, develop, and maintain scalable data pipelines in AWS using AWS Glue, Python, and PySpark. Build robust data ingestion frameworks to collect and process data from multiple on-premises and cloud-based sources. Implement Change Data Capture (CDC) solutions for near real-time data synchronization and replication. Utilize AWS Database Migration Service (AWS DMS) to migrate and replicate data across enterprise systems with minimal downtime. Design and implement event-driven architectures using Kafka, Amazon SNS, Amazon SQS, and EventBridge. Develop cloud-native data processing solutions supporting high availability, scalability, and performance. Build, optimize, and maintain enterprise Data Lake solutions. Monitor and troubleshoot data workflows using AWS CloudWatch and AWS CloudTrail. Develop efficient Python-based data processing applications leveraging libraries such as Pandas and NumPy. Work with relational and NoSQL databases including SQL Server, DynamoDB, MongoDB, and Cassandra. Support migration and modernization of legacy data pipelines into AWS-based architectures. Collaborate with business stakeholders, application owners, and data teams to understand data architecture, business requirements, and analytics needs. Document data models, ETL processes, data flows, and target-state architectures. Drive continuous improvements in data quality, platform performance, security, and operational efficiency.