AWS Data Engineer

Overview:

Job Title: AWS Data Engineer

Location: Charlotte, NC

Job Type: Full-Time

Experience: 8-10 Years

Job Summary

We are seeking an experienced AWS Data Engineer to design, build, and optimize scalable, event-driven data platforms on AWS. The ideal candidate will have strong expertise in AWS data services, real-time streaming architectures, ETL development, and Infrastructure as Code (Terraform). This role will focus on building high-performance data pipelines supporting fraud detection, analytics, and customer engagement platforms.

Required Skills

AWS Data Engineering

• Strong hands-on experience with:
  • AWS Lambda
  • Amazon S3
  • Amazon EventBridge
  • Amazon Kinesis (Data Streams & Firehose)
  • AWS Glue (ETL & Crawlers)
  • AWS Step Functions
  • Amazon Athena
  • Amazon Connect
  • Amazon Macie
• Experience designing and implementing AWS Data Lake architectures

Programming & Data Processing

• Strong proficiency in:
  • Python
  • PySpark
• Experience developing:
  • ETL/ELT Pipelines
  • Data Transformation Workflows
  • Real-Time Data Processing
• Hands-on experience with:
  • Parquet File Format
  • Glue Crawlers
  • AWS Glue Data Catalog

Streaming & Event-Driven Architecture

• Experience with:
  • Event-Driven Architecture
  • Publish/Subscribe (Pub/Sub) Models
  • Apache Kafka
  • Amazon EventBridge
  • Kinesis Data Streams
  • Kinesis Firehose

DevOps & Infrastructure

• Hands-on experience with:
  • Terraform (Infrastructure as Code)
  • CI/CD Pipelines
  • Cloud Automation
• Experience deploying and managing AWS infrastructure

Data Analytics & Security

• Experience using:
  • Amazon Athena
  • AWS Glue Catalog
  • Amazon Macie
• Strong understanding of:
  • Data Governance
  • Data Security
  • Data Integrity
  • Performance Optimization

Key Responsibilities

• Design and implement scalable AWS-based data engineering solutions
• Develop real-time event-driven architectures using EventBridge, Kafka, and Kinesis
• Build and optimize ETL pipelines using AWS Glue, Python, and PySpark
• Configure and manage AWS Glue Crawlers for automated schema discovery and metadata management
• Design and maintain data lakes using Amazon S3, Parquet, Glue Catalog, and Athena
• Develop integrations between Customer Profiles, messaging platforms, and downstream systems
• Build automated workflows using AWS Step Functions
• Provision and manage AWS infrastructure using Terraform
• Implement CI/CD pipelines for automated deployment and infrastructure management
• Perform end-to-end testing, monitoring, troubleshooting, and performance tuning
• Optimize cloud architecture for scalability, reliability, cost efficiency, and security
• Maintain technical documentation, architecture diagrams, and operational runbooks

Preferred Qualifications

• Experience in fraud detection or financial services platforms
• AWS Certifications (Solutions Architect, Data Engineer, or Developer Associate)
• Experience with:
  • Lakehouse Architectures
  • Streaming Analytics
  • Cloud-Native Data Platforms
• Knowledge of DevOps best practices and Infrastructure Automation