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Apptoza Inc. in Toronto, ON, seeks a Principal Consultant – AWS Data Platforms & Agentic AI to lead tech vision and hands-on engineering for enterprise data platforms and Agentic AI solutions.
You will architect scalable data lakehouse patterns, semantic layers, and secure agent-data access across AWS services, while guiding engineers through implementation and optimization.
Role - Principal Consultant – AWS Data Platforms & Agentic AI
Location - Toronto, ON
Principal Consultant – AWS Data Platforms & Agentic AI
We are looking for a Principal Consultant – AWS Data Platforms & Agentic AI to provide technical leadership in architecting, building and scaling next-generation enterprise Data and Agentic AI platforms.
This is a senior, hands-on technology leadership role requiring a rare combination of AWS Data architecture, Agentic AI expertise, engineering depth and executive presence.
You should be equally comfortable presenting a technology vision to CTOs and Managing Directors, defining Reference Architectures/HLDs/LLDs, leading technical workshops, and working directly with engineers to solve complex design, implementation, and performance issues.
This is not a strategy-only architecture role. Strong hands-on engineering capability is essential.
Lead architecture and engineering across Enterprise Data Platforms, Data Fabric, Data Products, Data Marketplace, BI and Agentic AI.
Define scalable Lakehouse and Medallion Architecture patterns for data ingestion, processing, storage, governance and consumption.
Architect Semantic Layers, Ontologies and Knowledge Graphs, including Amazon Neptune, to support analytics and Agentic AI.
Design secure Agentic AI solutions using Amazon Bedrock Agent Core, Runtime, Gateway, Identity and Model Context Protocol (MCP).
Establish patterns for Agent Identity, authentication, authorization, entitlements and governed agent-to-data access.
Build identity and entitlement architecture across IAM, IAM Identity Center, Cognito, Lake Formation, S3, Glue, Athena and Quick Sight.
Design fine-grained data security, including RLS/CLS, data governance, guardrails and access observability.
Industrialize Amazon QuickSight through dataset automation, SPICE optimization, security integration and platform governance.
Establish enterprise Agent telemetry, observability and evaluation across agents, models, MCP/tool calls and data access.
Define reusable Reference Architectures, HLDs, LLDs, engineering standards and implementation guardrails.
Lead architecture workshops, technical deep-dives and design reviews with engineering and senior leadership.
You will:
You are neither a strategy-only Enterprise Architect nor solely a delivery-focused Data Engineer.
You bring together:
Architecture Depth | Hands-on Engineering | Data & Agentic AI Vision | Executive Presence
You can articulate the future of Enterprise Data and Agentic AI to senior executives, translate that vision into detailed architecture, and then work alongside engineering teams to build, troubleshoot and optimize the solution.
You don't just define the architecture. You help build it and make it work in production.