Job Title: Sr.Data Engineer (Mid–Senior Level) – AWS & StreamingExperience Level – 13-15+ YearsLocation: Fort Mill, SC (3 days hybrid)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:
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Develop and maintain scalable ETL/ELT pipelines using AWS Glue, PySpark, and Python
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Build event-driven workflows using AWS Lambda
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Design and manage real-time streaming solutions using Kafka, KSQL, and Apache Flink
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Implement and enforce comprehensive data quality frameworks, including validation, profiling, monitoring, and reconciliation
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Optimize data processing performance, scalability, reliability, and cost in cloud environments
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Collaborate with cross-functional teams to deliver reliable, production-grade data platforms and ensure data integrity across the pipeline
Must have Skills:
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Strong hands-on experience with Python and PySpark
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Proven expertise in AWS Glue, Lambda, and other cloud-native data services
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Solid experience with the Kafka ecosystem (topics, partitions, consumer groups, streaming patterns)
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Demonstrated experience building and supporting data quality frameworks (validation rules, reconciliation checks, profiling, anomaly detection)
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Strong understanding of distributed data processing and scalable architecture patterns
Good-to-Have Skills:
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Experience with Apache Flink for real-time stream processing and stateful computations
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Knowledge of KSQL or other streaming SQL engines
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Exposure to CI/CD pipelines, IaC (Terraform/CloudFormation), and DevOps practices
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Familiarity with data lake/lakehouse architectures and table formats such as Iceberg, Delta, or Hudi
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Experience working in enterprise or financial data environments