Senior Data & AI Platform Engineer

What We Do
We help organizations adopt, govern and manage Microsoft 365 with beautiful, compelling and innovative software. Our Orchestry tool is a leading platform that manages over 500,000 Microsoft teams each month across multiple customers, geographies and verticals.

How Are We Different?
Orchestry isn't just a run-of-the-mill Microsoft partner that is creating a product on the side. We are 100% a product-led organization that values innovation and best practices from inside and outside of Microsoft to create great software. We have long-lasting relationships with partners and customers. We are fearless and innovative. We believe that there is too much poor, un-intuitive software built for Microsoft 365 administrators and users.

Our goal is to change that.

Who We Are
We only hire and want to work with the best in the world. Our team is composed of Microsoft MVPs, founders of successful startups and those with a burning desire to make a difference. Headquartered in Canada we don't care who you are or where you live. If you want to build a great career and work with the best then get in touch.

About the Role
Are you the kind of data engineer who sees a warehouse and thinks “this should power decisions and automation, not just dashboards”? Have you built production-grade AI systems that actually reason over real company data instead of toy examples? If so, this role is for you.

Orchestry is hiring a  Senior Data & AI Platform Engineer  to own and evolve our Microsoft Fabric–based Data Warehouse and turn it into the foundation for secure, agentic AI workflows across the company.

This is a platform ownership role. The Fabric warehouse isn’t just for reporting, it’s the backbone for reliable, governed data, AI-accessible context, and intelligent internal automation. You’ll sit at the intersection of Data Engineering and Applied AI, building the infrastructure and agentic systems that help every department make better decisions. This is not a BI dashboard role and not an experimental AI sandbox.

Success comes from production-level thinking, strong software instincts, and the ability to build systems that scale responsibly across the business.

What You'll Be Doing
Data Warehouse Ownership (Microsoft Fabric)

Own and evolve Orchestry’s Fabric-based Data Warehouse as the trusted foundation for analytics and AI.

Design and implement scalable data models, transformations, and refresh strategies

Establish data quality checks, lineage, and trust signals

Partner with Engineering and Product to onboard new data sources

Define warehouse patterns that are reliable, understandable, and AI-consumable

Monitor and optimize Fabric capacity usage, storage growth, refresh schedules, and query performance

Ensure the data platform scales sustainably as adoption increases

AI-Ready Data Architecture

Design the warehouse not just for reporting, but for reasoning.

Create schemas and semantic layers optimized for retrieval, aggregation, and temporal analysis

Build curated datasets and feature-like abstractions for AI consumption

Develop secure, scalable retrieval pipelines (RAG-style patterns) across structured and unstructured data

Ensure governed access paths so AI agents don’t query raw, unstructured chaos

Embed lineage, trust signals, and validation checks into downstream AI workflows

Agentic Workflows & Internal AI Systems
Internal Agentic Workflows

Develop internal AI agents that query the warehouse, interpret results, and recommend or take action

Create automation workflows across

Usage analysis

Engineering and product signal

Build reusable frameworks for internal agents, including tool orchestration, prompt management, and workflow execution

Integrate AI systems with internal platforms to enable automated actions and intelligent recommendations

Develop evaluation approaches to measure agent accuracy, reliability, and business impact

Customer-Facing AI Agents

Design and build customer-facing AI agents that reason over customer environment data and take actions using Orchestry’s product capabilities through defined tool interfaces

Define tool schemas, action boundaries, and safety guardrails for autonomous agent execution, including tenant data…