Real Estate Data Integration Engineer (MRI, Argus & SS&C Integration)

Title: Senior Microsoft Fabric Data Engineer (MRI, Argus & SS&C Integration)
Location: Remote
Length: 1 Year+

Out of scope: Integration beyond MRI, Argus, SS&C  ·  Investor PII processing  ·  Real-time GL reporting  ·  Change management beyond core working sessions.
 
Key Requirements
•    MRI experience — Have you built MRI ingestion pipelines before? Describe your specific MRI/MIX API experience and which modules and endpoints you have worked with. This is a differentiator question.
•    MRI MIX API — three open questions vendors must address: (1) Does the Client’s MIX license cover GL history, charges, and sales history endpoints? This is a pre-engagement gate — not a Week 3 test. (2) Are Client-specific custom fields exposed via API? (3) Are any relied-upon fields encrypted at the DB level? State your approach and contingency for each.
•    Incremental sync — MRI data changes daily. Delta loads are required — not nightly full refreshes. Describe your incremental sync approach for MRI and how you handle late-arriving or changed records.
•    Schema ownership — Client must own the data model schema, all dimensional model design, and all Fabric artifacts produced. Vendor retains no IP in what is built. Confirm this explicitly and describe how schema documentation is delivered.
•    Documentation standard — ''''Handoff docs'''' is not a deliverable. The SOW must name specific artifacts: data dictionary, pipeline runbooks, and transformation logic documentation at a standard sufficient for a third party to operate the environment. Describe your documentation approach and format.
•    Named internal owner — Client must designate an internal owner who is trained to operate and maintain the platform post-engagement. The engagement must include explicit knowledge transfer sessions with that person — not just documentation. Describe how you structure this.
•    Argus Add-On — VDI-hosted automation required to remove manual laptop dependency. If you believe the direct Argus API is viable and cost-competitive, make the case.
•    SS&C — Schema-drift tolerant ingestion required. Historical archive volume and variation is uncharacterized — state your assumptions explicitly.
•    AI / MCP connectivity — Can the Fabric lakehouse be queried by an external AI agent? This may require a custom MCP server layer on top of Fabric. Confirm whether you have built this pattern before and whether it is in scope. AI connectivity is a must-have — not an elective capability.
•    Security — SOC 2 Type 2 required before system access is granted. Client data may not be used for AI/ML training or benchmarking. All AI tools used in service delivery must be disclosed.
•    Fabric SKU — Which SKU do you recommend for production workloads covering all three source systems, AI queries, and Power BI? Provide your estimated monthly OpEx at that SKU.