Chief Cloud Data Architect

4 days ago

Kurnool, Andhra Pradesh, India beBeeCloudDataEngineer Full time US$ 1,80,000 - US$ 2,00,000
Cloud Data Engineer

We are seeking a highly skilled Cloud Data Engineer to join our team. As a key member of our data engineering group, you will play a critical role in designing and implementing scalable cloud-based data solutions.

The ideal candidate will have extensive experience in building and managing large-scale data warehouses, data lakes, and data integration systems on cloud platforms like Google Cloud Platform (GCP) and Amazon Web Services (AWS).

You will lead multiple data engagements on GCP cloud for data lakes, data engineering, data migration, data warehouse, and business intelligence. Interface with multiple stakeholders within IT and business to understand the data requirements. Take complete responsibility for the successful delivery of all allocated projects on parameters of Schedule, Quality, and Customer Satisfaction.

About the Role:
  • Design and implement end-to-end data pipelines and data integration solutions for structured and unstructured data sources and targets.
  • Develop expertise in various data integration and ETL technologies on cloud like Spark, Pyspark/Scala, Dataflow, DataProc, EMR, etc.
  • Maintain deep knowledge of one or more cloud and on-premise databases like Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, SQL Server, etc.
  • Familiarity with No-SQL databases like MongoDB, CouchDB, Cassandra, GraphDB, etc.
Skills and Qualifications:
  • More than 8 years of experience in technical, solutioning, and analytical roles.
  • 5+ years of experience in building and managing data lakes, data warehouses, data integration, data migration, and business intelligence/artificial intelligence solutions on cloud.
  • Ability to understand business requirements, translate them into functional and non-functional areas, define non-functional boundaries in terms of Availability, Scalability, Performance, Security, Resilience etc.
  • Experience in architecting, designing, and implementing end-to-end data pipelines and data integration solutions for varied structured and unstructured data sources and targets.
  • Well-versed with various data integration, and ETL technologies on cloud like Spark, Pyspark/Scala, Dataflow, DataProc, EMR, etc.
  • Good understanding of Cloud solutions for Iaas, PaaS, SaaS, Containers and Microservices Architecture and Design.
  • Ability to compare products and tools across technology stacks on Google, AWS, and Azure Cloud.
  • Understanding of Security features and Policies in one or more Cloud environments like GCP/AWS/Azure.
Preferred Experience:
  • Preferred experience of having worked on Machine Learning Frameworks like TensorFlow, Pytorch, etc.

The preferred candidate should have good understanding of Cloud solutions for Iaas, PaaS, SaaS, Containers and Microservices Architecture and Design, and ability to compare products and tools across technology stacks on Google, AWS, and Azure Cloud.

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