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Sr. Data Engineer AWS & Streaming - Full Time

Sabio infotechCharlotte, NC🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationCharlotte, NC, United States
SQLApache SparkAWSETLFlinkApacheCloudFormationKafkaPythonTerraformCI/CD

Job description

Job Title: Sr. Data Engineer – AWS & Streaming
Location: Fort Mill SC/Charlotte, NC/New York, NY (2-3 Days Hybrid)
Position: Full-Time
Duration: 6+ Months to Long Term
Experience level – 10+ 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

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