Job Requirement :

- Have Implemented and Architected solutions on Google Cloud Platform using the components of GCP

- Experience with Apache Beam/Google Dataflow/Apache Spark in creating end to end data pipelines.

- Experience in some of the following : Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning.

- Experience programming in Hadoop, python, SQL

- Expertise in at least two of these technologies: Relational Databases, Analytical Databases, NoSQL databases.

- Certified in Google Professional Data Engineer/ Solution Architect is a major Advantage

Skills Required :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Design, develop, and deploy scalable ETL/ELT pipelines using PySpark on GCP.

- Utilize GCP services extensively, including BigQuery (data warehousing), Cloud Storage, Dataproc, and Dataflow.

- Optimize PySpark jobs for performance and reliability, and fine-tune BigQuery queries.

- Implement complex transformations and process large volumes of structured/unstructured data using Spark SQL and PySpark

- Build and manage automated workflows using Apache Airflow or Cloud Composer.

- Strong proficiency in Python and SQL is essential

- Proven experience with Google Cloud Platform (GCP) services.

- Relevant certifications on google cloud is an added advantage.