Job Description :
Implement end-to-end data analytics solutions (from data ingestion, storage, processing, analysis/ exploration through visualization) for large-scale, complex client environments on the Google Cloud Platform.
Work on data migrations and transformational projects, and with customers to design large-scale data processing systems,
Capture and share best practices amongst the Healthcare and Life Sciences Solution Architects / Solution Consultants.

Minimum Qualifications: 

GOOGLE CLOUD CERTIFIED Professional Data Engineer
3+ years of experience in leading implementation of highly scalable data management systems.
2 years experience in Architecting, Developing, and deploying scalable enterprise data analytics solutions (Enterprise Data Warehouses, Data Marts, etc
Experience across multiple big data platforms, ETL, data modeling, and business intelligence big data architectures.
Hands-on experience deploying data analytics solutions in GCP using a combination of BigQuery, CloudSQL, Cloud Storage, Cloud Dataflow, Cloud Datalab, Cloud Dataproc, Cloud Pub/ Sub.
Demonstrated skills in leadership, communication, analysis, problem solving and short term and long term planning.
Excellent interpersonal and organizational skills, ability to handle diverse situations, multiple initiatives and rapidly changing priorities.
Must be a self-starter who requires minimal supervision.

Preferred Qualifications: 

Healthcare Domain expertise:  Strong Experience in HL7/FHIR data standards, HIPAA, PHI, ISO, GDPR and other global healthcare compliance/regulatory requirements.
Experience with ingestion and processing of large Genomic, Digital, EMR, EHR, Omics, Imaging data sets coming from different data sources.
Experience with healthcare related platforms such as Epic Cache/Chronicles, Clarity, Cerner, etc. 
Experience in one or more of Hadoop, data mining, machine learning, data visualization and statistical modeling
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