Cloud Data Architect- Google Cloud Platform

Hi, Hope you are doing well and healthy. Please find below job description for your reference and let me know your interest.

• Partner with product managers and product owners to understand business needs and develop architecture patterns and blueprints that can be built by the engineers
• Collaborate with internal and external stakeholders for designing and building application architecture and components
• Own and drive business and technology conversations along with customer architecture group
• Create, present, and deliver data and platform solutions, roadmaps, and featured use cases at customer meetings, working sessions, educational sessions, and events
• Mentor and guide the Mphasis team on overall solutioning, architecture and delivery
• Help build a culture of learning and innovation with a focus on learning new technologies / practices and spearheading adoption within the organization
• Bring a passion to stay on top of tech trends, experiment with and learn new technologies, participate in technology communities and act as an internal mentor to users of these platforms

• Be client facing in advising them on =P optimized architectures for data management, help develop roadmaps for on-prem to Cloud migration effort

• Minimum 8 years’ experience in data warehouse/data engineering with strong hands-on experience in ETL
• Candidate must have at least 5-6 years’ experience of designing solutions on =P
• Experience on at least 1 sizeable =P project as an Architect, preferably both data migration from on-prem to cloud
• Must have implemented at least 2 end to end data warehouses

• Must have very strong SQL experience, Data modelling
• Candidate should know following services and have worked hands-on Google BigQuery, Google Cloud Storage, Google Dataflow, CloudSQL, Google Cloud Dataproc, Google Pub/Sub, Sqoop, Pyspark and any other relevant services
• Processed data loading in Bigquery from Google cloud storage using =P Dataproc. Scheduling end to end using =P cloud composer service. Maintaining BQ datasets for reporting requirements
• Building and maintaining data catalog in =P
• Provisioning system, user and data level security for data in transit and rest
• Expertise managing and working with large databases, data management ,including understanding of various data structures and common methods in data transformation, data validation and audit