Architects data pipelines, LLM integration patterns, and security/governance models on Azure. Owns the hard questions about where data lives, how it moves, who can see it, and how AI features stay inside the tenant boundary.
What you'll do
Day-to-day
Design and implement data pipelines on Azure (Data Factory, Synapse, Functions, Event Hubs) for client automation and analytics use cases.
Build integration layers between ERP SQL databases and reporting/AI tools: live connections, cached extracts, and governed data flows.
Architect LLM integration patterns using Azure OpenAI Service: model orchestration, prompt management, output validation, and cost optimization, all within the client tenant boundary.
Implement Azure AI Document Intelligence for OCR workflows: invoice processing, field document digitization, and extraction pipelines.
Define data security and governance models: access controls, encryption, audit logging, data minimization, and environment boundaries. Commercial data does not leave the M365 tenant.
Build and maintain ML/AI infrastructure for classification, summarization, and extraction workflows.
Advise on data architecture decisions across client engagements, including ERP schema design, storage strategy, and integration patterns.
Support compliance and security reviews for clients in regulated or data-sensitive industries.
What we're looking for
You should
5+ years of data engineering experience with significant depth in Azure cloud services.
Understand ML/LLM deployment patterns at a production level, not just prototyping. Experience with Azure OpenAI Service preferred.
Can design and implement data security architectures: role-based access, encryption at rest and in transit, audit trails, and least-privilege principles.
Comfortable working with ERP and operational databases: job cost data, phase codes, equipment records, HR records, financial reporting.
Think in systems. You see how data flows across an organization and can spot where it breaks, leaks, or bottlenecks.
Communicate technical architecture decisions clearly to both engineering teams and non-technical stakeholders.
Comfortable in a fractional/advisory capacity where you may design systems that others implement.
Nice to have
Bonus points
Experience with construction, manufacturing, or project-based business data (Viewpoint Vista, Procore, HCSS)
Experience with Microsoft 365 data integration (Graph API, Dataverse, SharePoint as a data layer)
Familiarity with Azure AI Document Intelligence for OCR and document processing
Experience building RAG architectures and retrieval-augmented generation patterns over enterprise knowledge bases
Background in regulated industries or contexts where data governance is non-negotiable
Interested?
Tell us what you build. If there's a fit, we'll bring you onto the next engagement that needs your skills.