GCP Data Engineer

We are looking for an experienced GCP Data Engineer with strong hands-on expertise in Google Cloud Platform, BigQuery, DBT, and Apache Airflow. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and transformation workflows for analytics and business intelligence platforms.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines on GCP.
• Build and optimize data transformation workflows using DBT (Data Build Tool).
• Develop and manage ETL/ELT pipelines using Apache Airflow.
• Work extensively with Google BigQuery for data ingestion, transformation, modeling, and optimization.
• Develop efficient SQL queries and optimize BigQuery performance and costs.
• Build reusable DBT models, tests, macros, snapshots, and documentation.
• Create and maintain Airflow DAGs for scheduled and event-driven data workflows.
• Integrate data from multiple sources including databases, APIs, files, and cloud applications.
• Implement data quality checks, validation, monitoring, and error handling.
• Design data models suitable for analytics, reporting, and BI use cases.
• Work with GCP services such as Cloud Storage (GCS), Cloud Composer, Pub/Sub, Dataflow, Cloud Functions, and IAM.
• Monitor pipeline performance and troubleshoot data engineering issues.
• Implement best practices for data security, governance, reliability, and scalability.
• Collaborate with Data Scientists, BI Developers, Analysts, Software Engineers, and business stakeholders.

Required Skills

• 4+ years of experience in Data Engineering.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Excellent knowledge of BigQuery.
• Strong experience with DBT / DBT Core or DBT Cloud.
• Strong experience with Apache Airflow and DAG development.
• Advanced SQL skills.
• Strong experience in Python for data engineering and automation.
• Experience developing ETL/ELT pipelines.
• Good understanding of data warehousing concepts and dimensional data modeling.
• Experience with Git and CI/CD practices.
• Understanding of data quality, testing, monitoring, and pipeline orchestration.