GCP Data Engineer

Purple Drive

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profile Job Location:

Jersey, NJ - USA

profile Monthly Salary: Not Disclosed
Posted on: 20 days ago
Vacancies: 1 Vacancy

Job Summary

Job Posting:GCP Data Engineer

We are seeking an experienced GCP Data Engineer with a strong background in data engineering cloud technologies and optimization. The ideal candidate will have expertise in Google BigQuery specifically in data ingestion performance optimization and data modeling. A deep understanding of cloud services such as Cloud Data Flow Pub/Sub and data orchestration tools like Apache Airflow is essential.

Key Responsibilities:

  • Design develop and maintain efficient data pipelines and workflows in Google Cloud Platform (GCP).

  • Optimize data ingestion processes and enhance performance in BigQuery.

  • Implement and manage real-time data streaming using Pub/Sub and Cloud Data Flow.

  • Develop and automate workflows using Apache Airflow.

  • Collaborate with cross-functional teams to design scalable and reliable cloud solutions.

  • Utilize Python and other tools for scripting and automation of data processes.

  • Apply DevOps principles for continuous integration and deployment (CI/CD) using GitHub and related tools.

Requirements:

  • Proven expertise in Google BigQuery including data modeling and performance optimization.

  • Strong experience with Cloud Data Flow Pub/Sub and Apache Airflow.

  • Proficient in Python for data engineering tasks.

  • Familiarity with DevOps practices and CI/CD pipelines.

  • Experience using GitHub for version control and automation.

  • Strong problem-solving and communication skills with the ability to work in a fast-paced collaborative environment.

Job Posting:GCP Data Engineer We are seeking an experienced GCP Data Engineer with a strong background in data engineering cloud technologies and optimization. The ideal candidate will have expertise in Google BigQuery specifically in data ingestion performance optimization and data modeling. A deep...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala