Overview

We're looking for a highly capable data engineering and architecture professional with a forward-looking mindset toward artificial intelligence. This individual will be responsible for designing and owning a modern data and AI ecosystem that supports how our company retrieves, interprets, and leverages commercial property data. This position will be the driving force behind our conversational data initiative - enabling users to interact with data through natural language.

In this role, you will establish and manage a centralized data environment built on Microsoft Fabric/OneLake, construct controlled ingestion frameworks from systems such as Yardi, SharePoint, CoStar, GreenStreet, Argus, and others, and develop intelligent agents and interfaces that allow non-technical users to explore portfolio data without relying on dashboards or coding. Close collaboration with IT, FP&A, and additional cross-functional partners will be required to define data needs and deliver a dependable, governed, AI-enabled data foundation.

The successful candidate brings a hands-on builder mentality, strong proficiency in Python and SQL, familiarity with vector-based data approaches, and background working with enterprise-scale cloud data ecosystems. Experience in commercial real estate is helpful but not essential-what's critical is the ability to quickly understand business domains and translate them into scalable data solutions.

Key Responsibilities

• Design and deploy a centralized, cloud-based data platform using Microsoft Fabric/OneLake.
• Develop structured, governed pipelines to ingest data from platforms such as Yardi, DataFreedom, SharePoint, Argus, CoStar, GreenStreet, Measurabl, and related systems.
• Create and implement conversational AI solutions and smart agents leveraging Microsoft Copilot and Azure AI technologies within a secure Microsoft 365 environment.
• Enforce data integrity through validation rules, schema controls, and quality monitoring at ingestion points.
• Act as the core data engineering partner for analytics teams, ensuring a strong and reliable data layer for BI consumption.
• Advocate for responsible adoption of AI and emerging tools within secure, enterprise-approved environments.
• Manage permissions, governance standards, and auditability across the full data ecosystem.
• Enable business users through training on AI-driven tools and natural language data access.

Core Areas of Work

Data Platform & Integration (Approx. 35-45%)

• Build and manage the centralized Fabric/OneLake platform, including components such as lakehouse structures, Delta tables, Dataflow Gen2 processes, and DirectLake models.
• Create controlled ingestion frameworks from multiple internal and third-party data systems, including ERP, document repositories, and external data providers.
• Ensure robust data validation, rule enforcement, and quality checks prior to promotion into authoritative datasets.
• Develop standardized data models that unify disparate sources, anchored by a consistent property master reference.
• Maintain governance structures, including documentation, lineage tracking, and change control procedures.
• Transition existing BI models from on-prem infrastructure to cloud-native solutions, eliminating dependency risks.

AI Enablement & Automation (Approx. 35-45%)

• Develop and deploy AI-enabled tools and conversational interfaces using Azure AI and Copilot technologies, ensuring all activity remains within secure tenant boundaries.
• Build and sustain conversational AI assistants integrated with collaboration tools such as Teams and Outlook, supported by vector-based search over structured and unstructured datasets.
• Design and implement integrations (APIs and connectors) that allow AI systems to access both structured and document-based data.
• Automate recurring workflows and operational processes (report distribution, validations, notifications) using Power Automate and Python.
• Continuously evaluate and adopt emerging AI capabilities while adhering to governance and security-first principles.

Security & Data Governance (Ongoing)

• Configure and maintain access management for workspaces and AI services, aligned with identity and policy frameworks.
• Ensure AI outputs respect user permissions, with security controls applied at the query level.
• Preserve auditability through version tracking within the data platform.
• Collaborate with IT leadership to ensure compliance with internal data governance, privacy, and security requirements.

Business Intelligence Collaboration (Approx. 10-20%)

• Partner closely with BI resources to define upstream data requirements and ensure data accuracy at its source.
• Support and maintain dashboards during the transition to the new platform.
• Enable AI-assisted analytics capabilities within the BI environment.
• Educate and guide stakeholders on using AI-driven and conversational data tools.

Experience & Background

• Bachelor's degree in a technical or data-related discipline (e.g., Computer Science, Information Systems, Analytics).
• Several years of relevant experience in data engineering, analytics engineering, or platform-focused BI roles.
• Proven track record building production-grade pipelines in cloud environments such as Fabric, Azure Data Lake, Databricks, or similar.
• Experience creating AI-driven solutions using large language models beyond simple prompting (e.g., retrieval-augmented generation, vector indexing, API integrations).
• Industry exposure to real estate or finance is helpful but not mandatory.
• Strong grounding in data structures, modeling practices, and pipeline design methodologies.
• Familiarity with integrations and automated workflows.

Technical Capabilities

• Fabric / OneLake: lakehouse implementations, pipeline orchestration, Delta tables, semantic modeling.
• SQL: advanced querying and data structure knowledge across database types.
• Python: scripting for data processing, automation, and API interaction with maintainable code practices.
• AI Technologies: experience with enterprise LLM ecosystems (Azure OpenAI, AI Search, Copilot tooling, or similar).
• Power BI: reporting, modeling, and administrative capabilities.
• Automation Tools: workflow orchestration and integration using Power Automate.
• APIs: design and consumption of REST services and custom connectors.
• Source Control: Git-based versioning practices.

Highly Valued Additions

• Exposure to SharePoint advanced content processing tools (e.g., document classification and metadata extraction).
• Experience with commercial real estate data platforms (Yardi, CoStar, Argus, etc.).
• Knowledge of data governance frameworks, lineage tracking, and stewardship principles.
• Familiarity with identity management and security enforcement within cloud environments.
• Relevant certifications in Microsoft Fabric or willingness to obtain.

Key Strengths

• A proactive builder who can translate ideas into functional systems without complete specifications.
• Strong focus on security, compliance, and governance from the start.
• Ability to quickly learn new business domains and apply them to data architecture.
• Effective collaborator across technical and business teams.
• Skilled at simplifying complex technical concepts for non-technical audiences.
• Commitment to clear documentation and building maintainable, scalable solutions.