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Skills

Amazon Web Services
Cloud Computing
Data Engineering
Glue
Lambda
Data Lake
Streaming
Hadoop
AI Agent
Snowflake
Airflow
Terraform
Data Validation

Summary

Job Title: Sr.Data Engineer– AWS & Streaming

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

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

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91112738
Position Id: 9036242
Posted 13 hours ago

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Deepthi Myana

Recruiter @ Sabio infotech

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AWS Data Engineer

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