GCP Data Engineer

Key Responsibilities:

• Design, build, and optimize scalable ETL/ELT pipelines using 

  PySpark

   on both Hadoop and GCP environments.
• Utilize Hadoop ecosystem components including 

  Hive

  , 

  HDFS

  , 

  YARN

  , and 

  Oozie

   for data storage, processing, and workflow orchestration.
• Implement and manage GCP data services such as 

  BigQuery

  , 

  Cloud Storage

  , 

  Dataflow

  , and 

  Cloud Composer

   to support data ingestion, transformation, and analytics workloads.
• Ensure the performance, scalability, and reliability of data pipelines to meet business and operational requirements.
• Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand data needs and deliver high-quality data solutions.
• Monitor and troubleshoot data pipelines, proactively addressing issues to minimize downtime.

Required Qualifications:

• Bachelors degree in Computer Science, Information Technology, or a related field (or equivalent work experience).
• 4 to 9 years of hands-on experience in data engineering or related roles.
• Proficiency in 

  PySpark

   programming and writing complex 

  SQL

   queries.
• Strong experience working with Hadoop ecosystem tools: 

  Hive

  , 

  HDFS

  , 

  YARN

  , and 

  Oozie

  .
• Practical knowledge of Google Cloud Platform data services including 

  BigQuery

  , 

  Dataflow

  , 

  Cloud Storage

  , and 

  Cloud Composer

  .
• Demonstrated ability to build scalable and reliable data pipelines in distributed environments.
• Excellent analytical, problem-solving, and communication skills.