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Senior AWS EMR Engineer - Immediate Joiners

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Senior AWS EMR Engineer - Immediate Joiners

Web Spiders

Senior AWS EMR Engineer - Immediate Joiners

Skills

Big DataData EngineeringAWS LambdaMachine LearningAIScalaAWSPySparkApache AirflowHadoop

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹3,000,000 / year

Location:

Kolkata, West Bengal, India

Work mode:

Remote

Published on:

17 August 2026

What they need


Web Spiders is looking for a Senior AWS EMR Engineer with strong hands-on experience in AWS EMR, Apache Spark, Hadoop, and large-scale distributed data processing.

The ideal candidate will have experience building, managing, optimizing, and troubleshooting production-grade data processing workloads on AWS, with a strong understanding of EMR clusters, Spark workloads, data pipelines, performance optimization, scalability, reliability, and cost efficiency.

If AWS EMR + Spark/Hadoop is your core expertise, we'd love to hear from you.

5+ Years Experience | Kolkata /Hybrid/Remote

Core Stack: AWS EMR • Apache Spark • Hadoop • S3 • Glue • Airflow/MWAA • Step Functions

* Immediate joiners preferred.*

Working Hours: Ability to work in the US Eastern Time Zone. Depending on project requirements, this may be adjusted to a half-day IST + half-day US EST schedule.

What You'll Do:

  • Design, develop, deploy, and optimize large-scale data processing workloads using AWS EMR and Apache Spark.
  • Build and maintain distributed data processing solutions using Spark/Hadoop.
  • Develop and optimize Spark jobs for performance, scalability, reliability, and cost efficiency.
  • Work with PySpark/Scala for distributed data processing and transformation.
  • Configure and manage EMR clusters based on workload and processing requirements.
  • Optimize Spark applications, including resource utilization, partitioning, joins, caching, and execution performance.
  • Troubleshoot EMR, Spark, Hadoop, and production data-processing issues.
  • Work with Amazon S3 as a scalable data lake/storage layer.
  • Integrate EMR workloads with AWS services such as Glue, Lambda, Step Functions, and Airflow/MWAA.
  • Monitor data-processing workloads and implement appropriate logging, error handling, and operational controls.
  • Optimize cloud workloads for performance, scalability, reliability, and AWS cost.
  • Collaborate with Data Engineering, Cloud, AI/ML, and Product teams to deliver reliable data-processing solutions.

Must-Have Skills:

  • 5+ years of hands-on experience in Data Engineering / Big Data Engineering.
  • Strong hands-on experience with AWS EMR.
  • Strong experience with Apache Spark and distributed data processing.
  • Strong understanding of Hadoop ecosystem and distributed computing concepts.
  • Strong programming experience with PySpark and/or Scala.
  • Experience working with Amazon S3 and AWS-based data lakes.
  • Experience troubleshooting and optimizing Spark/EMR workloads.
  • Strong understanding of ETL/ELT concepts and large-scale data processing.
  • Experience with production data pipelines and performance optimization.

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