AWS Data Platform Architect
thermofisher
Job Description
Platform Architecture & Strategy
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Define and evolve the target AWS data platform architecture across ingestion, storage, transformation, semantic, and consumption layers
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Establish and enforce architecture standards for scalability, security, reliability, and cost efficiency
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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)
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Ensure platform evolution introduces new capabilities without disrupting existing reporting and analytics workloads
AI & Graph Enablement
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Design and implement AI/LLM-ready architecture patterns, including RAG-based retrieval and semantic data access
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Develop and integrate graph data models to support relationship-driven analytics and intelligence use cases
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Ensure the platform supports efficient data access patterns for AI workloads, across structured, semi-structured, and graph data
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Lead proofs-of-concept and reference implementations to validate AI and graph capabilities prior to production adoption
Platform Ownership & Optimization
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Provide architectural oversight for Redshift, Databricks, and Athena, ensuring performance optimization, workload governance, and cost efficiency
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Guide and review complex SQL transformations and workloads, ensuring scalability and performance across large datasets
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Ensure Power BI and semantic layers are aligned to governed, high-quality datasets
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Identify and resolve architecture-level bottlenecks impacting performance, cost, or reliability
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Maintain architecture documentation, standards, and technical decision records
Governance, Security & Operations
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Implement and enforce data governance standards, including dataset certification, access control, and usage consistency
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Define and manage IAM roles, encryption, and security controls across AWS environments
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Ensure production stability through structured rollouts, validation, and change management practices
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Monitor and continuously optimize platform performance and cost efficiency
Leadership & Collaboration
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Drive adherence to architectural best practices across engineering and analytics teams through standards, reviews, and guidance
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Translate business and analytics requirements into scalable, future-ready technical designs
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Partner with Data Engineering, BI, and platform teams to ensure consistent implementation across all layers
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Support technical capability building through documentation, reviews, and knowledge sharing
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