| Location | Atlanta, GA |
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Data Architect
Remote in Georgia, & 4 others
Solution Architecture
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We are seeking a Staff Consultant to serve as a long-term, full-time resident Data Architect supporting our customers data foundation. This role focuses on enabling and operating Amazon SageMaker Unified Studio, building and optimizing serverless data pipelines, managing modern data lake storage formats, and integrating agentic AI services to support data rendering and analytics.
The position spans data platform engineering, self-service analytics enablement, and BI delivery through Quick Suite, all aligned with AWS cloud-native best practices.
Responsibilities
Configure, manage, and support Amazon SageMaker Unified Studio (SMUS), including 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, while managing IAM domains, access policies, and governance configurations
Architect and maintain the customers data foundation on AWS, ensuring scalability, governance, and performance
Design and optimize data lake architectures using Amazon S3, including modern storage formats (Parquet, Iceberg, Delta), and implement data cataloging, partitioning, and lifecycle management strategies for large-scale environments
Integrate Amazon OpenSearch Service for search, analytics, and data exploration use cases
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 tooling 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 to support 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 with emphasis 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
Requirements
7+ years of experience in data architecture and engineering roles, preferably within 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 modern storage formats (Parquet, Iceberg, Delta)
Skills in Data Foundation Architecture, covering catalog, governance, and self-service enablement
Familiarity with Amazon OpenSearch Service for search, analytics, and data exploration
Proficient communication skills in English (B2 level or higher)
Nice to have
Knowledge of Quick Suite / Amazon QuickSight
Understanding of Agentic AI Services (e.g., Bedrock Agents, AgentCore)
Competency in Amazon Lake Formation
Skills in Infrastructure as Code (CDK, Terraform)
Strong knowledge of Python