Data Engineer - GCP

Responsibilities:
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.
Requirements:
Must Have: GCP + Scala + Kafka or Pub/Sub.
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, Hadoop, Spark, SQL, BigQuery, Bigtable, 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.
Certification as a Google Professional Data Engineer/Solution Architect is a major Advantage.
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 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, BigQuery, Bigtable, Cloud Storage, Datastore, Spanner, Cloud SQL, and Machine Learning.
Experience programming in Java, Python, etc.
Advanced SQL writing and experience in data mining (SQL, ETL, data warehouse, etc. ) and using databases in a business environment with complex datasets.

Experience
5-9 yrs