Software Engineer-II

Coforge; Dadri; Hybrid; INR 1,400,000 - 2,100,000; Full time

Job summary

Coforge is seeking a skilled Data Engineer with strong experience in Python, AWS, ETL and PySpark to build and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate should have hands-on experience in data ingestion, transformation, optimization, and large-scale data processing on AWS platforms.

You will design, develop, and optimize data pipelines, collaborate with cross-functional teams, and contribute to data quality and governance initiatives.

Qualifications

• 5–10 years of experience in data engineering.
• Hands-on with AWS data services and PySpark.
• Experience building scalable ETL/ELT pipelines.
• Experience with cloud data platforms.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build data processing solutions using PySpark and Python.
• Develop and support AWS-based data platforms using AWS Glue, S3, Lambda, Redshift, EMR, and Athena.
• Implement data integration, cleansing, validation, and transformation processes.
• Optimize ETL jobs for performance, scalability, and reliability.
• Work with structured and semi-structured datasets from multiple sources.
• Develop reusable frameworks, libraries, and data quality checks.
• Monitor and troubleshoot production data pipelines.
• Collaborate with architects, analysts, and business stakeholders to understand data requirements.
• Participate in code reviews, deployments, and production support activities.

Skills

Python

Data engineering

ETL

PySpark

Tools

AWS

Glue

S3

Lambda

Redshift

EMR

Athena

PySpark

Job description

Role & responsibilities

Data Engineer Python Developer + AWS + ETL + PySpark

Data Engineer Python, AWS, ETL & PySpark
Experience: 5-10 Years
Location: Pune / Hyderabad / Bengaluru / Noida
Employment Type: Full-Time

Job Summary

We are looking for a skilled Data Engineer with strong experience in Python, AWS, ETL, and PySpark to build and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate should have hands‑on experience in data ingestion, transformation, optimization, and large‑scale data processing on AWS platforms.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build data processing solutions using PySpark and Python.
• Develop and support AWS-based data platforms using AWS Glue, S3, Lambda, Redshift, EMR, and Athena.
• Implement data integration, cleansing, validation, and transformation processes.
• Optimize ETL jobs for performance, scalability, and reliability.
• Work with structured and semi-structured datasets from multiple sources.
• Develop reusable frameworks, libraries, and data quality checks.
• Monitor and troubleshoot production data pipelines.
• Collaborate with architects, analysts, and business stakeholders to understand data requirements.
• Participate in code reviews, deployments, and production support activities.