Google Cloud Platform data engineer with Java Development and telecom - Dallas, TX

Innovative It Solutions - Dallas, TX

Full-time - Mid Level

Dallas, TX

Professional, Scientific, and Technical Services

About the position

The Google Cloud Platform Data Engineer role focuses on designing, developing, and maintaining data pipelines and ETL processes specifically for handling large volumes of data on Google Cloud Platform. This position requires collaboration with cross-functional teams to understand data needs and implement scalable solutions, utilizing various Google Cloud tools and Java development for data processing and integration.

Responsibilities

• Design, develop, and maintain data pipelines and ETL processes on Google Cloud Platform for handling large volumes of data.
• Collaborate with cross-functional teams to understand data needs and design scalable solutions.
• Work with Google Cloud Platform tools such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Dataproc for data processing and storage.
• Utilize Java to develop, enhance, and optimize applications and scripts for data ingestion, transformation, and integration.
• Develop data models and ensure data quality, performance, and reliability across the data pipeline.
• Implement best practices for data governance, security, and compliance on the cloud.
• Debug and optimize Java applications and ETL jobs to ensure smooth operation.
• Participate in code reviews and adhere to software development best practices.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 6+ years of experience as a Data Engineer or in a similar role, with a focus on Google Cloud Platform.
• Strong proficiency in Google Cloud Platform services, including BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Dataproc.
• Solid Java development experience, including familiarity with frameworks such as Spring or Hibernate.
• Experience in designing and implementing ETL processes and data pipelines.
• Knowledge of data warehousing, data lakes, and database management principles.
• Familiarity with SQL and data modeling.
• Understanding of CI/CD pipelines, version control (Git), and other DevOps practices.