data architect

Описания нет

• Configure, manage, and support Amazon SageMaker Unified Studio (SMUS), including its data catalog, blueprints, and serverless compute capabilities
• Enable self-service data discovery, exploration, and analysis for business and technical users through SMUS
• Design and maintain SMUS blueprints and templates for repeatable, governed data workflows, and manage IAM domains, access policies, and governance configurations
• Architect and maintain the customer's AWS data foundation, ensuring scalability, governance, and performance
• Design and optimize data lake architectures using Amazon S3 and modern storage formats, and implement cataloging, partitioning, and lifecycle management strategies for large-scale environments
• Integrate Amazon OpenSearch Service for search, analytics, and data exploration
• Build and optimize serverless data pipelines using AWS Glue and AWS Lambda, including ETL/ELT jobs for data ingestion, transformation, and delivery
• Ensure pipeline reliability, monitoring, and error handling using AWS-native tools such as CloudWatch, Glue job metrics, and S3 analytics
• Support the integration and delivery of Quick Suite (QuickSight / QuickSight Q) for analytics, dashboards, and self-service reporting
• Integrate agentic AI services for intelligent data rendering, automated insights, and data-driven decision-making, collaborating with AI/ML teams to connect agentic workflows with the data foundation
• Apply AWS Well-Architected Framework principles, focusing on security, reliability, performance efficiency, and cost optimization
• Document data architectures, SMUS configurations, pipeline designs, and operational runbooks, and conduct regular knowledge transfer sessions to build internal capability

• 7+ Years of experience in data architecture and engineering roles, preferably in AWS cloud environments
• Expertise in Amazon SageMaker Unified Studio, including catalog, blueprints, and serverless compute
• Proficiency in AWS Glue, AWS Lambda, and serverless compute for data workflows
• Background in data lake architectures and Amazon S3 with Parquet, Iceberg, and Delta storage formats
• Skills in data foundation architecture, including catalog, governance, and self-service enablement
• Familiarity with Amazon OpenSearch Service for search, analytics, and data exploration
• English proficiency at B2 level or higher
• Будет плюсом: Knowledge of Quick Suite / Amazon QuickSight, understanding of agentic AI services (e.g., Bedrock Agents, AgentCore), competency in Amazon Lake Formation, Infrastructure as Code (CDK, Terraform), strong knowledge of Python

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