Description

Build and maintain scalable data pipelines on Google Cloud Platform using BigQuery, dbt, and Airflow.

This role is hybrid.

Responsibilities

• Design and implement data pipelines on GCP, leveraging BigQuery for storage, querying, and analytics.
• Build and maintain dbt models for data transformations, ensuring correctness, reusability, and maintainable project structure.
• Orchestrate end-to-end workflows using Apache Airflow, including scheduling, dependency management, and failure handling.
• Develop and optimize SQL-based transformations and analytics-ready datasets in BigQuery with attention to performance and cost.
• Implement data quality checks and monitoring patterns to ensure pipeline reliability and timely issue detection.

Required Skills

• 5-10 years of relevant experience in data engineering and analytics pipelines.
• Strong proficiency with Google Cloud Platform (GCP) for building and operating cloud data pipelines.
• Expertise in BigQuery for analytics data modeling, querying, and performance optimization.
• Hands-on experience with dbt (data build tool) for transformation workflows and version-controlled data modeling.
• Proficiency in Apache Airflow for orchestration, scheduling, and operational reliability of data pipelines.
• Strong SQL skills for writing and optimizing queries and transformations.

Preferred Skills

• Python for pipeline utilities, automation, and data processing support.

Key Skills

Education

Any Graduate