Big Data Engineer - Scala Mandatory

Coforge; Hyderabad, Pune District, Greater Noida; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Coforge is hiring Big Data Engineers to design and develop large-scale data processing solutions using Spark and Scala. The role focuses on building robust ETL pipelines on AWS, handling batch and streaming data, and ensuring performance, scalability, and reliability across enterprise data platforms.

We are seeking professionals with 4 to 10 years of experience in Spark, Scala, SQL, and AWS technologies, with locations in Hyderabad, Pune, and Greater Noida.

Qualifications

• Experience designing and building large-scale data processing solutions using Spark and Scala.
• Proficiency in ETL and data ingestion pipelines on AWS.
• Experience with batch and streaming data processing frameworks.

Responsibilities

• Design and develop large-scale data processing solutions using Spark and Scala.
• Build robust ETL and data ingestion pipelines on AWS.
• Work with batch and streaming data processing frameworks.
• Optimize data workloads for performance, scalability, and reliability.
• Collaborate with cross-functional teams to deliver enterprise-grade data solutions.

Skills

Spark

Scala

SQL

AWS EMR

AWS S3

AWS Glue

Hive

Tools

Kinesis

Lake Formation

CloudFormation

API Gateway

Job description

Coforge Hiring is Big Data Engineers || Spark, Scala & AWS || 4 to 10 Years || Hyderabad, Pune & Greater Noida

We are looking for talented Big Data professionals who are passionate about building scalable data platforms and high-performance data processing solutions on AWS.

Job Location: Hyderabad, Pune & Greater Noida Only.

Skills: Spark, Scala, SQL, AWS EMR, AWS S3, AWS Glue, Hive.

Good to Have: Kinesis, Lake Formation, CloudFormation, API Gateway.

What You'll Do:

• Design and develop large-scale data processing solutions using Spark and Scala.
• Build robust ETL and data ingestion pipelines on AWS.
• Work with batch and streaming data processing frameworks.
• Optimize data workloads for performance, scalability, and reliability.
• Collaborate with cross-functional teams to deliver enterprise-grade data solutions.