Gcp Data Engineer

Coforge; Greater Noida; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Coforge is seeking a Data Engineer to design, develop, and optimize data pipelines on Google Cloud Platform. You will work with cross-functional teams to build scalable, production-grade data solutions using PySpark and Python.

The role emphasizes strong SQL skills, data modeling, and implementing the Medallion Architecture across Bronze-Silver-Gold with BigQuery, Dataproc, and Cloud Composer.

Qualifications

• 4+ years of hands-on data engineering experience.
• Expertise in PySpark and Python.
• Advanced proficiency in SQL and query optimization.
• Production-grade big data pipelines on Google Cloud Platform (GCP).
• Experience implementing Medallion Architecture (Bronze-Silver-Gold).

Responsibilities

• Design, develop, and maintain scalable, production-grade data pipelines and ETL/ELT workflows.
• Build high-performance data processing solutions using PySpark and Python.
• Write complex and optimized SQL queries for large-scale datasets.
• Develop efficient, reliable, and reusable data engineering frameworks and components.
• Implement and maintain data models aligned with Medallion Architecture principles.
• Work with GCP services such as BigQuery, Dataproc, Cloud Composer (Airflow), Pub/Sub, and Cloud Run.
• Ensure data quality, performance, scalability, and operational excellence across data platforms.
• Collaborate with business and technical stakeholders to translate requirements into robust data solutions.
• Troubleshoot, optimize, and continuously improve existing data pipelines and workflows.

Skills

Data engineering

Tools

PySpark

Python

SQL

BigQuery

Dataproc

Cloud Composer (Airflow)

Pub/Sub

Cloud Run

Medallion Architecture

ETL/ELT pipelines

Job description

Data Engineer (GCP)

About the Role

We are looking for a highly motivated and results-driven Data Engineerwho thrives on solving complex data challenges and building scalable, production-grade data platforms.

You will work closely with cross-functional teams to design, develop, and optimize modern data pipelines on Google Cloud Platform (GCP), enabling data-driven decision-making across the organization.

Key Responsibilities

• Design, develop, and maintain scalable, production-grade data pipelines and ETL/ELT workflows.
• Build high-performance data processing solutions using PySparkand Python.
• Write complex and optimized SQLqueries for large-scale datasets.
• Develop efficient, reliable, and reusable data engineering frameworks and components.
• Implement and maintain data models aligned with Medallion Architecture (Bronze, Silver, Gold)principles.
• Work with GCP services such as BigQuery, Dataproc, Cloud Composer (Airflow), Pub/Sub, and Cloud Run.
• Ensure data quality, performance, scalability, and operational excellence across data platforms.
• Collaborate with business and technical stakeholders to translate requirements into robust data solutions.
• Troubleshoot, optimize, and continuously improve existing data pipelines and workflows.

Required Skills & Qualifications

• 4+ years of hands-on experience in Data Engineering.
• Strong expertise in PySparkand Python.
• Advanced proficiency in SQLand query performance optimization.
• Proven experience building and supporting production-grade big data pipelines.
• Strong understanding of modern data architecture and data engineering best practices.
• Hands-on experience with Google Cloud Platform (GCP), particularly:
• BigQuery
• Dataproc
• Cloud Composer (Airflow)
• Pub/Sub
• Cloud Run
• Experience implementing Medallion Architecture (Bronze-Silver-Gold).