Must Have:
Expertise in Google Data Engineering services Big Query, Dataproc etc
Strong experience in programming languages such as Python, PySpark data manipulation and engineering tasks.
Expertise in SQL and NoSQL databases
In-depth knowledge of data warehousing solutions
Deep understanding on data warehousing concepts
Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using tools like Apache Airflow, Talend, or Informatica.
Valuable to Have:
Understanding of DevOps Concepts in GCP.
Solid understanding of data modeling concepts and techniques to create productive and scalable data models.
Experience with version control systems such as Git for code management and collaboration.
Knowledge of data governance, data quality standards, and data security practices to ensure compliance and protection of sensitive information