Manager, Enterprise Data and Analytics

Nutrition International•Ottawa, ON

7d•CA$106,000 - CA$118,000•Hybrid

About The Position

Reporting to the Principal Enterprise Architect, the Manager, Enterprise Data & Analytics, is responsible for the design, implementation, and operational management of Nutrition International’s enterprise data and reporting solutions. The role focuses on transforming architectural direction into reliable data pipelines, models, and analytics-ready datasets that enable trusted reporting, dashboards, and future AI initiatives. The Manager ensures that enterprise data assets are accurate, auditable, and fit for decision-making across Corporate Services, HR, Business Development, Programs, and across NI globally.

Requirements

Bachelor’s or Master’s degree in Data Engineering, Computer Science, Information Systems, or related field
At least 5 to 8 years of experience in data architecture, analytics engineering, or enterprise reporting.
Strong expertise in SQL, data modeling, master data management (MDM) and data warehouse/lakehouse concepts.
Hands-on experience with Power BI, Fabric, Azure data services, NSAW, Snowflake, and modern ETL / data pipeline technologies or equivalent platforms.
Demonstrated experience with AI-enabling data practices, including Retrieval-Augmented Generation (RAG), vector databases, embedding pipelines, context engineering, and AI integration protocols such as Model Context Protocol (MCP).
Practical knowledge of preparing and governing enterprise data for consumption by large language models (LLMs), AI agents, and intelligent automation tools.
Strong familiarity with AI/ML frameworks, prompt engineering concepts, agentic AI architecture, and advanced data analytics.
Fluency in English is essential.

Nice To Haves

Working capacity in French is an advantage.

Responsibilities

Design, implement, and maintain enterprise data models aligned with architectural standards and governance rules.
Develop and manage data models, views, and transformations supporting the Unit's needs.
Maintain databases and NI Datawarehouse.
Design data architectures that support AI-ready data access, including structured knowledge bases, contextual retrieval layers, and vector-enabled data stores for Retrieval-Augmented Generation (RAG) and agentic AI workflows.
Collaborate with the Systems Administrator on environment configuration, security, and access requirements for data platforms (databases, Datawarehouse, tables…).
Build and maintain data pipelines that feed AI/ML models and intelligent assistants, including contextual data preparation for RAG systems, embedding generation, and integration with AI tooling via protocols such as Model Context Protocol (MCP).
Deliver clean, trusted datasets optimized for Power BI and NI future enterprise reporting tools.
Translate business reporting needs into scalable and reusable data structures.
Enrich NI's reporting maturity by implementing KPIs, aggregations, and metrics in data layers wherever possible.
Enable AI-augmented analytics by preparing datasets for natural language querying, contextual AI assistants, and automated insight generation, ensuring data is structured, semantically tagged, and accessible to AI agents.
Work closely with the Principal Enterprise Architect to operationalize enterprise architecture and data standards.
Collaborate with IM, Risk and Assurance, and other governance stakeholders to support auditability, compliance, and traceability.