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Gcp Data Engineer

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Description

Data Engineer (GCP)


About the Role

We are looking for a highly motivated and results-driven Data Engineer who thrives on solving complex data challenges and building scalable, production-grade data platforms.


You will work closely with cross-functional teams to design, develop, and optimize modern data pipelines on Google Cloud Platform (GCP), enabling data-driven decision-making across the organization.


Key Responsibilities

  • Design, develop, and maintain scalable, production-grade data pipelines and ETL/ELT workflows.
  • Build high-performance data processing solutions using PySpark and Python.
  • Write complex and optimized SQL queries for large-scale datasets.
  • Develop efficient, reliable, and reusable data engineering frameworks and components.
  • Implement and maintain data models aligned with Medallion Architecture (Bronze, Silver, Gold) principles.
  • Work with GCP services such as BigQuery, Dataproc, Cloud Composer (Airflow), Pub/Sub, and Cloud Run.
  • Ensure data quality, performance, scalability, and operational excellence across data platforms.
  • Collaborate with business and technical stakeholders to translate requirements into robust data solutions.
  • Troubleshoot, optimize, and continuously improve existing data pipelines and workflows.

Required Skills & Qualifications

  • 4+ years of hands-on experience in Data Engineering.
  • Strong expertise in PySpark and Python.
  • Advanced proficiency in SQL and query performance optimization.
  • Proven experience building and supporting production-grade big data pipelines.
  • Strong understanding of modern data architecture and data engineering best practices.
  • Hands-on experience with Google Cloud Platform (GCP), particularly:
    • BigQuery
    • Dataproc
    • Cloud Composer (Airflow)
    • Pub/Sub
    • Cloud Run
  • Experience implementing Medallion Architecture (Bronze-Silver-Gold).

Skills

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See also

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