About the role

We are looking for an experienced Data Engineer with strong expertise in Google Cloud Platform (GCP) to join our growing data engineering team. The ideal candidate will have a solid background in designing and managing scalable data pipelines, data storage, and cloud-native infrastructure, while collaborating with cross-functional teams to deliver reliable and secure data solutions.

Key responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines using GCP services such as Dataflow, Cloud Functions, Pub/Sub, and BigQuery.
• Build and optimize scalable data storage and warehousing solutions using Cloud Storage, BigQuery, and Cloud SQL.
• Implement best practices for data modeling, transformation, and orchestration to ensure reliability and scalability.
• Establish and enforce data governance, security, and access controls using GCP IAM and other native tools.
• Collaborate with data scientists, analysts, and business teams to ensure timely and accurate data availability.
• Monitor and optimize GCP costs, performance, and resource utilization.
• Troubleshoot and resolve issues related to data ingestion, transformation, and performance bottlenecks.

Qualifications

• 4–7 years of experience in Data Engineering, with a minimum of 2 years of hands-on experience in GCP.
• Proficiency in Python, PySpark SQL, and data modeling best practices.
• Strong experience with ETL/ELT pipelines, data lakes, and cloud-native services in GCP.
• Working knowledge of data warehousing and distributed computing frameworks.
• Familiarity with Infrastructure-as-Code tools such as Terraform (preferred).
• GCP Certification (Data Engineer or Architect) is a strong plus.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.

Experience: 4 to 7 years