Big Data Engineer & Big Data Lead ( Spark, Scala & AWS )

Coforge; Hyderabad, Pune District, Greater Noida; On-site; INR 1,200,000 - 3,000,000; Full time

Job summary

Coforge is hiring for experienced Big Data Engineers and Leads to join our Data Engineering team in Hyderabad, Pune, and Greater Noida. The role focuses on Spark, Scala, and AWS to design and optimize large-scale data platforms and ETL pipelines.

Ideal candidates have 3–10 years of experience with hands-on cloud data technologies, data processing, and data quality practices to deliver scalable solutions for critical business initiatives.

Qualifications

• 3–10 years of experience in Big Data engineering or similar roles.
• Strong expertise in Apache Spark and Scala.
• Proficiency with AWS services and cloud data platforms.
• Experience designing, developing and optimizing ETL pipelines.

Responsibilities

• Design, develop, and maintain large-scale distributed data processing applications using Spark and Scala.
• Build and enhance data ingestion, transformation, and ETL pipelines using AWS services.
• Develop scalable data solutions for structured and unstructured datasets.
• Create reusable frameworks for large-scale data processing.
• Implement cloud-native data solutions leveraging AWS like EMR, S3, Glue, Lambda.
• Build batch and real-time streaming apps and optimize Spark jobs.

Skills

Big Data

Apache Spark

Scala

AWS

Job description

Coforge is Hiring Big Data Engineers & Big Data Leads.

Note: Immediate Joiners Preferred.

Coforge Ltd. is looking for experienced Big Data Engineers and Big Data Leads with strong expertise in Spark, Scala, and AWS to join our growing Data Engineering team.

Experience:- 3 to 10 Years

Mandatory Skills:- Apache Spark, Scala & AWS Services

Job Locations:- Hyderabad, Pune & Greater Noida

Overview

We are seeking highly skilled Big Data professionals with hands-on experience in Spark, Scala, and AWS cloud technologies. The ideal candidate will be responsible for designing, developing, and optimizing large-scale data processing solutions, building enterprise-grade ETL pipelines, and delivering scalable data platforms that support critical business initiatives.

Key Responsibilities

Data Engineering & Development

• Design, develop, and maintain large-scale distributed data processing applications using Spark and Scala.
• Build and enhance data ingestion, transformation, and ETL pipelines using AWS services.
• Develop highly scalable and reliable data solutions for structured and unstructured datasets.
• Create reusable frameworks and components for large-scale data processing.

Cloud Platform & AWS

Implement cloud-native data solutions leveraging AWS services such as:

EMR, S3, Glue, Lambda, Athena, Redshift, Kinesis, IAM, CloudWatch & Ensure security, governance, scalability, and cost optimization of cloud-based data platforms.

Data Processing

• Build batch and real-time streaming applications using Spark frameworks.
• Process and analyze high-volume datasets efficiently.
• Optimize Spark jobs for performance tuning, memory management, and execution efficiency.

Data Quality & Reliability

• Implement monitoring, logging, and alerting mechanisms.
• Ensure data quality, consistency, and integrity across data platforms.
• Troubleshoot production issues and provide timely resolutions.