GCP Data Engineer

Job Summary

We are seeking an experienced GCP Data Engineer to design, build, and optimize our scalable cloud data platform. In this role, you will architect real-time and batch ELT/ETL data pipelines, manage data lakes and enterprise warehouses, and ensure seamless integration across our cloud environment. You will collaborate closely with analytics and engineering teams to transform complex raw data into reliable, high-performance data assets.

• Design, deploy, and maintain scalable data pipelines using Google Cloud Platform (GCP) services like Big Query, Cloud Dataflow, Pub/Sub, Dataproc, and Cloud Storage (GCS).
• Build automated ETL/ELT workflows using orchestration tools such as Cloud Composer (Apache Airflow) or Prefect
  .
• Optimize query performance, schema design, and partitioning strategies in Big Query for large-scale datasets.
• Ingest and process structured, semi-structured, and unstructured data streams in both real-time and batch modes.
• Implement robust data security, governance, quality checks, and access controls across cloud data assets.
• Write clean, efficient, and well-tested code in Python, PySpark, or SQL
  .

• Experience: 6+ years of hands-on data engineering experience, with a strong focus on native GCP data stack components.
• Core Tech Stack: Deep proficiency in Big Query
  , Cloud Dataflow (Apache Beam),
  Pub/Sub
  , SQL
  , and Python/Py Spark .
• Big Data & Streaming: Solid understanding of distributed computing, real-time streaming architectures, and data modeling (Kimball, Star Schema).
• CI/CD & Dev Ops:
  
  Experience with containerization (
  Docker/GKE
  ) and Infrastructure as Code (
  Terraform
  ) is a plus.
• Certifications: GCP Professional Data Engineer certification is highly desirable.