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About the role
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, pySpark/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: Overall experience - 6 to 8 years 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 Extensive hands-on experience with PySpark. Proven experience with Google Cloud Platform (GCP) services.
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