Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

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
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 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.

AWS Data Platform Architect (AI & Graph)