AWS Data Engineer

We are seeking an experienced AWS Data Engineer / Event-Driven Architecture Engineer to design, develop, and migrate near real-time fraud detection solutions from on-premises platforms to AWS cloud environments. The ideal candidate will have strong expertise in AWS data services, event-driven architectures, real-time data processing, Python, PySpark, Terraform, and CI/CD automation.The role involves building scalable data pipelines, implementing cloud-native architectures, integrating messaging platforms, optimizing data lake solutions, and ensuring secure, reliable, and high-performing AWS-based systems., * Develop and execute a comprehensive migration strategy for near real-time fraud detection campaigns from on-premises systems to AWS.

• Design and implement event-driven architectures using:
• Amazon EventBridge
• Apache Kafka
• Amazon Kinesis Data Streams
• Amazon Kinesis Firehose
• Build and maintain scalable data pipelines using:
• AWS Glue ETL Jobs
• AWS Glue Crawlers
• Python
• PySpark
• Develop data ingestion, transformation, and processing workflows for real-time and batch data workloads.
• Configure and manage AWS Glue Crawlers for automated schema discovery and AWS Data Catalog updates.
• Design and optimize data lake architectures using:
• Parquet-based storage
• Amazon Athena
• AWS Glue Data Catalog
• Implement integrations between customer profiles and messaging platforms to trigger automated profile updates and downstream workflows.
• Develop automation for fraud-related outbound call triggers based on customer profile events.
• Design and orchestrate complex processing workflows using AWS Step Functions.
• Provision, configure, and manage cloud infrastructure using Terraform (Infrastructure as Code).
• Implement secure, scalable, and cost-effective AWS solutions following cloud best practices.
• Develop and maintain CI/CD pipelines for automated deployment and resource management.
• Perform end-to-end testing to validate functionality, performance, reliability, and scalability.
• Monitor production systems, troubleshoot issues, and optimize application performance.
• Maintain technical documentation covering architecture, workflows, integrations, and operational procedures.

• Strong hands-on experience with AWS Cloud Services, including:
• AWS Lambda
• Amazon S3
• Amazon EventBridge
• Amazon Kinesis Data Streams
• Amazon Kinesis Firehose
• AWS Glue (ETL & Crawlers)
• AWS Step Functions
• Amazon Connect
• Amazon Athena
• Amazon Macie
• Strong programming experience in:
• Python
• PySpark
• Experience designing and developing:
• Real-time data processing systems
• Scalable data pipelines
• Event-driven architectures (Pub/Sub model)
• Strong knowledge of:
• AWS Glue Crawlers for schema discovery and cataloging
• AWS Data Lake architectures
• Parquet-based data storage optimization
• Hands-on experience with:
• Terraform Infrastructure as Code (IaC)
• CI/CD pipelines and automation frameworks
• Experience working with messaging platforms:
• Apache Kafka
• Amazon EventBridge
• Preferred Qualifications
• Experience migrating enterprise applications from on-premises environments to AWS.
• Experience building fraud detection, customer analytics, or real-time decisioning platforms.
• Knowledge of cloud security, governance, and compliance best practices.
• Experience optimizing AWS workloads for performance and cost efficiency.
• Familiarity with monitoring and operational tools in AWS environments.