Senior Data Engineer AWS & Streaming

Hybrid in New York, NY, US • Posted 5 hours ago • Updated 5 hours ago
Full Time
No Travel Required
Hybrid
$120,000 - $140,000/yr
Fitment

Dice Job Match Score™

🛠️ Calibrating flux capacitors...

Job Details

Skills

  • AWS
  • AWS Glue
  • PySpark
  • Python
  • ETL
  • SQL
  • Kafka
  • Spark
  • workflow orchestration

Summary

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: 10476889
  • Position Id: 9025044
  • Posted 5 hours ago
Contact the job poster
RD

Rahul Dalal

Recruiter @ Incedo Inc
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