Technical Requirements
- Have Implemented and Architected solutions on the 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, Hadoop, Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, and Machine Learning.
- Experience programming in Java, Python, etc.
- Expertise in at least two of these technologies: Relational Databases, Analytical Databases, and NoSQL databases.
- Certified in Google Professional Data Engineer/ Solution Architect is a major Advantage
Roles Responsibilities
Experience
- 6-8 years experience in IT or professional services experience in IT delivery or large-scale IT analytics projects
- Candidates must have expertise and knowledge of the 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, and 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.
Skills Required
Python, Hadoop, Spark, Sql