AWS Data Engineer

Job Title: Sr.Data Engineer– AWS & Streaming

Location: Fort Mill SC OR Charlotte, NC OR New York, NY (2-3 Days Hybrid)

Experience level – 10- 15 Years

Role Summary:
We are seeking a Mid–Senior Data Engineer with strong expertise in AWS-based data engineering, real-time streaming technologies, and enterprise-grade data quality frameworks. The ideal candidate will design, build, and optimize scalable batch and streaming data pipelines, implement robust data validation and monitoring processes, and support mission-critical analytics platforms. 

Key Responsibilities:

• Develop and maintain scalable ETL/ELT pipelines using AWS Glue, PySpark, and Python

• Build event-driven workflows using AWS Lambda

• Design and manage real-time streaming solutions using Kafka, KSQL, and Apache Flink

• Implement and enforce comprehensive data quality frameworks, including validation, profiling, monitoring, and reconciliation

• Optimize data processing performance, scalability, reliability, and cost in cloud environments

• Collaborate with cross-functional teams to deliver reliable, production-grade data platforms and ensure data integrity across the pipeline

 Required Skills:

• Strong hands-on experience with Python and PySpark

• Proven expertise in AWS Glue, Lambda, and other cloud-native data services

• Solid experience with the Kafka ecosystem (topics, partitions, consumer groups, streaming patterns)

• Demonstrated experience building and supporting data quality frameworks (validation rules, reconciliation checks, profiling, anomaly detection)

• Strong understanding of distributed data processing and scalable architecture patterns

 Good-to-Have Skills

• Experience with Apache Flink for real-time stream processing and stateful computations

• Knowledge of KSQL or other streaming SQL engines

• Exposure to CI/CD pipelines, IaC (Terraform/CloudFormation), and DevOps practices

• Familiarity with data lake/lakehouse architectures and table formats such as Iceberg, Delta, or Hudi

• Experience working in enterprise or financial data environments