Description

Design and migrate near real-time fraud detection systems from on-premises to AWS, owning the end-to-end architecture, implementation, and optimization.

This role is on-site.

Responsibilities

• Design event-driven architectures using Amazon EventBridge, Kafka, Kinesis, and Lambda to process fraud events.
• Build scalable data pipelines with AWS Glue, PySpark, and Python for ingestion, transformation, and ETL.
• Implement Infrastructure as Code using Terraform and manage CI/CD pipelines for deployment automation.
• Orchestrate complex workflows with AWS Step Functions and configure Glue Crawlers for schema discovery.
• Optimize data storage in Parquet format and enable querying via Amazon Athena while ensuring security and cost-efficiency.

Required Skills

• 5+ years of experience with AWS services including Lambda, S3, EventBridge, Kinesis, Glue, Step Functions, Athena, and Macie.
• Proficiency in Python and PySpark for data engineering and automation.
• Hands-on experience with Terraform for Infrastructure as Code.
• Strong understanding of event-driven architectures and Pub/Sub models.
• Experience building real-time data processing systems and data lake architectures.
• Familiarity with CI/CD tools and automation pipelines.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

• AWS Certified Developer or AWS Solutions Architect certification.
• Experience with Amazon Connect and integrating with messaging platforms.

Key Skills

Education

Bachelor's degree