AWS Data Platform Architect (AI & Graph)

Job description

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Position Summary We are seeking an experienced AWS Data Platform Architect to own and evolve our enterprise data platform. This role is responsible for designing a scalable, secure, and governed AWS-based data architecture that supports both current analytics and an AI-ready Data-as-a-Platform foundation. You will ensure the platform is AI-ready by design, embedding capabilities such as RAG patterns, semantic access, and graph-based data modeling, while maintaining operational stability of existing analytics workloads across Redshift, Databricks, Athena, and Power BI. This is a hands-on architecture leadership role that requires deep expertise in SQL, Python, and modern data platforms, with end-to-end ownership of data, analytics, and platform governance. Key ResponsibilitiesPlatform Architecture & StrategyDefine and evolve the target AWS data platform architecture across ingestion, storage, transformation, semantic, and consumption layers Establish and enforce architecture standards for scalability, security, reliability, and cost efficiency Design integration and migration patterns across legacy and modern platforms (Redshift, Databricks, Athena, Power BI/Fabric, and semantic layers such as Cube/SPOT where applicable) Ensure platform evolution introduces new capabilities without disrupting existing reporting and analytics workloads AI & Graph EnablementDesign and implement AI/LLM-ready architecture patterns, including RAG-based retrieval and semantic data access Develop and integrate graph data models to support relationship-driven analytics and intelligence use cases Ensure the platform supports efficient data access patterns for AI workloads, across structured, semi-structured, and graph data Lead proofs-of-concept and reference implementations to validate AI and graph capabilities prior to production adoption Platform Ownership & OptimizationProvide architectural oversight for Redshift, Databricks, and Athena, ensuring performance optimization, workload governance, and cost efficiency Guide and review complex SQL transformations and workloads, ensuring scalability and performance across large datasets Ensure Power BI and semantic layers are aligned to governed, high-quality datasets Identify and resolve architecture-level bottlenecks impacting performance, cost, or reliability Maintain architecture documentation, standards, and technical decision records Governance, Security & OperationsImplement and enforce data governance standards, including dataset certification, access control, and usage consistency Define and manage IAM roles, encryption, and security controls across AWS environments Ensure production stability through structured rollouts, validation, and change management practices Monitor and continuously optimize platform performance and cost efficiency Leadership & CollaborationDrive adherence to architectural best practices across engineering and analytics teams through standards, reviews, and guidance Translate business and analytics requirements into scalable, future-ready technical designs Partner with Data Engineering, BI, and platform teams to ensure consistent implementation across all layers Support technical capability building through documentation, reviews, and knowledge sharing QualificationsRequiredBachelor’s degree in Computer Science, Engineering, or related field 10+ years of experience in data architecture, data engineering, or cloud data platforms Proven experience designing and operating AWS-based enterprise data platforms Hands-on expertise with Redshift, Databricks, Athena, and Power BI in production environments Strong proficiency in SQL and Python, enabling development, optimization, and troubleshooting of data pipelines, queries, and cross-platform integrations Experience designing and implementing graph data models or graph databases Experience enabling or integrating AI/LLM use cases within data platforms Core SkillsAWS architecture and cloud-native data design principles Advanced SQL expertise, including query optimization, data modeling, and performance tuning on large-scale datasets Performance optimization across modern data platforms (Redshift, Databricks, Athena) Data governance and security, including IAM, access controls, and encryption Graph modeling and relationship-driven data design Batch and real-time data processing patterns Strong troubleshooting and system-level performance tuning Clear and structured architecture documentation and decision records PreferredExperience implementing CI/CD for data platforms AWS Professional-level certifications Familiarity with RAG architectures and LLM-driven data access patterns What You’ll DriveEvolution of a modern, unified AWS data platform aligned to a Data-as-a-Platform model Adoption of AI-ready data architecture, including RAG and semantic access patterns Integration of graph-based modeling into enterprise analytics and intelligence use cases Improved performance, governance, and cost efficiency across the data ecosystem Why This Role MattersThis role sits at the intersection of data platform architecture and next-generation AI enablement. You will shape how data is structured, accessed, and leveraged to support advanced analytics, intelligent applications, and scalable AI use cases, while ensuring the reliability and continuity of the existing data ecosystem.