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W2 Opportunity // GCP Data Engineer // Atlanta, GA (Atlanta)
W2 Opportunity // GCP Data Engineer // Atlanta, GA (Atlanta)CloudIngest • Atlanta, GA, United States
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W2 Opportunity / / GCP Data Engineer / / Atlanta, GA (Atlanta)

W2 Opportunity / / GCP Data Engineer / / Atlanta, GA (Atlanta)

CloudIngest • Atlanta, GA, United States
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Job Description : GCP Data Engineer

Location : Atlanta, GA (Hybrid)

Rate : $50 / hr. on W2 (No C2C)

Summary

We are seeking a highly skilled GCP Data Engineer to design, build, and optimize cloud-native data pipelines and analytics solutions on Google Cloud Platform. The ideal candidate has strong experience with Python , BigQuery , Cloud Data Fusion , and core GCP services such as Cloud Composer , Cloud Storage , Cloud Functions , and Pub / Sub . This role requires a strong foundation in data warehousing concepts and scalable data engineering practices.

Responsibilities

  • Design, develop, and maintain robust ETL / ELT pipelines on Google Cloud Platform .
  • Build and optimize data workflows using Cloud Data Fusion , BigQuery , and Cloud Composer .
  • Write efficient and maintainable Python code to support data ingestion, transformation, and automation.
  • Develop optimized BigQuery SQL for analytics, reporting, and large-scale data modeling.
  • Utilize GCP services such as Cloud Storage , Pub / Sub , and Cloud Functions to build event-driven and scalable data solutions.
  • Ensure data quality, governance, and reliability across all pipelines.
  • Collaborate with cross-functional teams to deliver clean, trusted, production-ready datasets.
  • Monitor, troubleshoot, and resolve performance issues in cloud data pipelines and workflows.

Must-Have Skills

  • Strong experience with GCP BigQuery (data modeling, SQL development, performance tuning).
  • Proficiency in Python for data engineering and pipeline automation.
  • Hands-on experience with Cloud Data Fusion for ETL / ELT development.
  • Working experience with key GCP services :
  • Cloud Composer
  • Cloud Storage
  • Cloud Functions
  • Pub / Sub
  • Strong understanding of data warehousing concepts , star / snowflake schemas, and best practices.
  • Solid understanding of cloud data architecture and distributed processing.

    • Good-to-Have Skills

  • Experience with Vertex AI for ML pipeline integration or model deployment.
  • Familiarity with Dataproc (Spark / Hadoop) for large-scale processing.
  • Knowledge of CI / CD workflows, Git, and DevOps best practices.
  • Experience with Cloud Logging / Monitoring tools.
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