AWS Data Engineer
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
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