Data Engineer; AI Engineering

About Metagenics
For over 43 years, Metagenics has had the mission to help people live happier, healthier lives through the life-changing power of nutrition.

We believe the way we do business is as important as the business we do; that a company in the nourishment business should nourish its people, too. So, we incorporated healthy, sustainable care into every dimension of our culture. Our diverse and expansive team are a prime example of the power of a people-first approach. We know first‑hand, when an organization prioritizes internal growth and fosters empathy, its people come together to set an example of what the world can become.

Join us in being the world’s leading healthcare professional-grade VMS company!

The Data Engineer is responsible for building and scaling the data and AI foundations that power the business

across North America. Based in the NAM region and reporting to the Global Data Engineering Manager, this role designs and operates modern data pipelines and AI-enabled solutions on Microsoft Azure and Microsoft Fabric, transforming data from ERP, commerce, marketing, and customer platforms into reliable, production‑grade products.

This is a hands‑on, delivery‑focused role at the intersection of data engineering and applied AI. The role partners closely with commercial, marketing, and technology stakeholders across the NAM region to accelerate growth, improve the customer experience and unlock new capabilities through data and AI.

• Data pipelines & platform:
  Design, build, and maintain scalable, reliable data pipelines and lakehouse solutions on Microsoft Fabric, Synapse Analytics, and Azure.
• AI engineering:
  Develop, integrate, and operationalize AI/ML and generative‑AI solutions — from feature pipelines and model deployment to RAG, embeddings, and LLM‑based applications — with a focus on production reliability.
• Data modeling & quality:
  Build well‑structured, governed data models; implement data quality, validation, lineage, and observability across the platform.
• Integration:
  Ingest and unify data from ERP (Dynamics 365 Finance & Operations), commerce, marketing automation, and CRM systems to create a trusted view of customers, products, and orders across the NAM region.
• Automation & MLOps:
  Apply CI/CD, infrastructure‑as‑code, orchestration, and MLOps practices to automate deployment, monitoring, and retraining.
• Partnership:
  Work with business and technical stakeholders across the NAM region, and with global data and technology teams, to translate commercial needs into data and AI solutions that drive measurable outcomes.
• Performance & cost:
  Optimize pipelines and workloads for performance, scalability, security, and cost efficiency in the cloud.
• Governance & security:
  Ensure solutions meet data governance, privacy, and security standards across the NAM markets in which we operate.

Experience / Training / Education

• 3–5 years in data engineering, with demonstrated delivery of production data and/or AI solutions.
• ERP (Dynamics 365 Finance & Operations):
  Working knowledge of D365 F&O (Fin Ops) — data entities, finance, sales, and supply chain modules, and how ERP data is extracted and modeled for analytics and reporting.
• Microsoft Fabric:
  Hands‑on experience delivering with Fabric — Lakehouse and Warehouse, Data Factory pipelines, Spark notebooks, semantic models, Mirroring, and Shortcuts. Awareness of capacity (CU / F‑SKU) consumption and cost management is highly valued.
• AI engineering:
  Practical experience designing, building, and deploying AI/ML solutions using Microsoft Foundry, Copilot Studio, large language models, embeddings, retrieval‑augmented generation (RAG), and production workflow integrations.
• Programming:
  Strong Python and…