Job Title: Data Engineer – GCP

Experience: 4 to 8 Years
Location: Bangalore / Pune / Hyderabad

Job Summary

We are looking for an experienced Data Engineer with strong expertise in Google Cloud Platform (GCP) to design, build, and maintain scalable data pipelines and analytics solutions. The ideal candidate should have hands-on experience with cloud data services, workflow orchestration, and strong SQL and scripting skills.

Key Responsibilities

• Design, develop, and maintain data pipelines on GCP
• Build and manage workflows using Apache Airflow
• Work extensively with BigQuery for data modeling, optimization, and complex SQL queries
• Manage and process data using Google Cloud Storage (GCS)
• Write efficient and reusable scripts using Python and Unix shell scripting
• Develop and optimize complex SQL queries for large datasets
• Ensure data quality, reliability, and performance of data systems
• Collaborate with data analysts, data scientists, and stakeholders to understand business requirements
• Troubleshoot and resolve data pipeline and performance issues

Required Skills & Qualifications

• 4–8 years of experience in data engineering or related roles
• Strong hands-on experience with GCP services (BigQuery, GCS, Airflow)
• Proficiency in Python and Unix/Linux scripting
• Expertise in writing and optimizing complex SQL queries
• Experience with ETL/ELT pipelines and data orchestration
• Good understanding of data warehousing concepts and best practices
• Strong problem-solving and analytical skills

Preferred Qualifications

• Experience with CI/CD for data pipelines
• Knowledge of data security and access management in GCP
• Experience working in Agile environments

Interested folks kindly fill the below form:
https://forms.gle/h3PgVmq8B8SrcUpW6

Job Types: Full-time, Permanent

Pay: ₹700,000.00 - ₹1,000,000.00 per year

Application Question(s):

• Could you please share your total years of work experience?
• What is your current CTC and your expected CTC
• Do you have hands-on experience with GCP?

Work Location: In person