Technical Requirements 

• 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: Python, c Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning. 

• Experience programming in Java, Python, etc. 

• 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 

Roles & Responsibilities 

Experience 

• Candidates must have expertise knowledge of Google Cloud Platform; the other cloud platforms are nice to have. 

• Expert knowledge in SQL development. 

• Expertise in building data integration and preparation tools using cloud technologies (like Snaplogic, Google Dataflow, Cloud Dataprep, Python, etc). 

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

• Experience in some of the following: Python, Hadoop, Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning. 

• Experience programming in Java, Python, etc. 

• Identify downstream implications of data loads/migration (e.g., data quality, regulatory, etc.) 

• Implement data pipelines to automate the ingestion, transformation, and augmentation of data sources, and provide best practices for pipeline operations. 

• Capability to work in a rapidly changing business environment and to enable simplified user access to massive data by building scalable data solutions 

• Advanced SQL writing and experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with complex datasets.