Work with implementation teams from concept to operations, providing deep technical subject matter expertise for successfully deploying large scale data solutions in the enterprise, using modern data/analytics technologies on premise and cloud.
Work with data team to efficiently use Google Cloud platform to analyze data, build data models, and generate reports/visualizations.
Integrate massive datasets from multiple data sources for data modelling.
Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with product management.
Design pipelines and architectures for data processing. Create and maintain machine learning and statistical models. Extract, Load, Transform, clean, and validate data.
Active Google Cloud Data Engineer Certification Hands on in designing, building and operationalizing large-scale enterprise data solutions and applications using one or more of GCP data and analytics services in combination with 3rd parties - Python, Pyspark, Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache Beam/ composer, Big Table, Cloud BigQuery, Cloud PubSub, Cloud storage Cloud Functions & Github.
Minimum of 7 year of designing and building production data pipelines from data ingestion to consumption within a hybrid big data architecture, using Cloud Native GCP, Python, SQL etc.
Minimum 7 year of hands-on GCP experience with a minimum of an end to end solution designed and implemented at production scale.