AWS Data Platform Architect (AI & Graph)

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 Responsibilities

Platform Architecture & Strategy

- Define 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 Enablement

- Design 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 & Optimization

- Provide 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 & Operations

- Implement 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 & Collaboration

- Drive 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

Qualifications

Required

- Bachelor’s degree in Computer Science, Engineering, or related field
- 8+ 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 Skills

- AWS 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

Preferred

- Experience implementing CI/CD for data platforms
- AWS Professional-level certifications
- Familiarity with RAG architectures and LLM-driven data access patterns

What You’ll Drive

- Evolution 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 Matters

This 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.