Design cloud-native data and AI architectures, including data lakes, warehouses, ETL/ELT pipelines, real-time streaming systems, and infrastructure as code. Review architectural patterns, optimize performance and costs, align delivery with business objectives, support client presentations and workshops, and mentor junior team members. The role requires cloud solution design experience across AWS or Azure, knowledge of data and AI patterns, AI algorithm evaluation, communication skills, and an AWS Certified Solutions Architect Professional certification.
About CloudThat:
At CloudThat, we are driven by our mission to empower professionals and businesses to harness the full potential of cloud technologies. As a leader in cloud training and consulting services in India, our core values guide every decision we make and every customer interaction we have.
Role Overview:
· Design and implement data lakes and data warehouses using cloud platforms.
· Choose appropriate storage solutions (e.g., Amazon S3, Azure Blob Storage, Google Cloud Storage).
Key Responsibilities:
· Design cloud-native data/AI architecture
· Review and guide development on architectural patterns
· Ensure delivery alignment with business objectives
· Support client presentations and technical workshops
· Manage junior team members and mentor in solutioning
Skills & Qualifications:
· Hands-on experience with cloud solution design (AWS, Azure)
· Strong grasp of data lake, data warehouse, and AI patterns
· Experience in AI algorithm design and evaluation
· Excellent communication and leadership potential
· AWS Certified Solution Architect Professional
Education: Any bachelor's degree
Technical Competencies:
· Build and orchestrate ETL/ELT pipelines using cloud-native tools (One of them):
o AWS: Glue, Lambda, Step Functions
o Azure: Data Factory, Synapse Pipelines
o GCP: Dataflow, Cloud Composer
· Set up and manage cloud-based data warehouses (one of them):
o AWS Redshift
o Azure Synapse Analytics
o Google BigQuery
· Optimize performance, partitioning, and cost-efficiency.
· Implement real-time data pipelines using (one of them):
o AWS Kinesis, Azure Event Hubs, Google Pub/Sub
o Stream processing with Apache Kafka, Apache Flink, or Spark Structured
Infrastructure as Code (IaC)
· Use tools like Terraform, AWS CloudFormation, or Azure Bicep to provision and manage cloud resources.
Behavioural Competencies:
· Leadership and Mentoring
· Business Acumen
· Communication Skills
Core Value Competencies:
Innovativeness
Proprietorship
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