AWS Data Platform Architect (AI & Graph)

Overview

Own and evolve the enterprise AWS data platform, designing a scalable, secure, and governed architecture that supports current analytics and an AI-ready Data-as-a-Platform foundation, while maintaining stability of existing analytics workloads.

What you'll do

• 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
• 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
• 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
• 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
• 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

What you'll need

• 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
• 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

Nice to have

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

Details

• Location: Bangalore, India
• Work schedule: Standard (Mon-Fri)
• Environmental conditions: Office