Qualifications

• 6+ years of hands-on data engineering experience, focusing on GCP data stack components.
• Deep proficiency in BigQuery, Cloud Dataflow, Pub/Sub, SQL, and Python/PySpark.
• Solid understanding of distributed computing and real-time streaming architectures.
• Experience with data modeling techniques like Kimball or Star Schema.
• Familiarity with Docker/GKE for containerization and Terraform for Infrastructure as Code is a plus.
• GCP Professional Data Engineer certification preferred.

Responsibilities

• Design, deploy, and maintain scalable data pipelines using GCP services like BigQuery and Cloud Dataflow.
• Build automated ETL/ELT workflows using tools such as Cloud Composer or Prefect.
• Optimize query performance and schema design for large datasets in BigQuery.
• Ingest and process various data streams in real-time and batch modes.
• Implement data security, governance, quality checks, and access controls.
• Write clean, efficient, and well-tested code in Python, PySpark, or SQL.

Benefits

• Opportunity to work on cutting-edge cloud data technologies.
• Collaborative environment with analytics and engineering teams.
• Flexibility to manage both real-time and batch data processing.
• Focus on designing scalable solutions for complex data challenges.
• Professional development through potential certifications.