Principal Data Architect

JLL•Chicago, IL

1d•$250,000 - $300,000•Remote

About The Position

JLL empowers you to shape a brighter way. Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Role Summary: We are seeking a hands-on Principal Data Architect to transform JLL's data consumption patterns. This role will drive the strategic vision for AI/BI, establishing practices for building semantic and context layers. As a senior individual contributor operating at the highest level of technical leadership, you will define how the organization transforms traditional analytics and enables AI-driven consumption use cases. The ideal candidate brings proven expertise in semantic modeling and enterprise ontology, context layer architecture, and transforming how business stakeholders consume and interact with information. In this role, you will partner closely with product and platform teams to build capabilities, collaborate with engineering teams to develop solutions, and drive adoption of enterprise data platform consumption patterns across the organization. We are looking for someone with proven hands-on experience who can champion core analytics and business personas, establish robust semantic layers for business line data, drive AI-powered self-service consumption, develop capabilities for reliable Text-to-SQL agents, and define new patterns for consuming data from the enterprise data platform (EDP).

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
12+ years of experience in enterprise data architecture, data engineering, or technology leadership roles.
Significant experience designing and implementing enterprise-grade AI/BI solutions in production environments.
Deep knowledge of modern data architecture patterns, including LLM-based data applications, RAG, data query agents, and serving data through MCP.
Expertise in distributed computing environments including Apache Spark, DBT, and ETL/ELT frameworks for large-scale data processing.
Proven experience building semantic layers and enterprise ontologies that enable AI-driven data consumption.
Strong understanding of data products, data contracts, data quality frameworks, and data authorization patterns.
Hands-on experience with cloud-native data platforms, specifically Databricks technology stack.
Experience establishing architecture standards, reference architectures, and technical guardrails across multiple teams.
Proven ability to influence senior technical and business stakeholders without direct authority.
Strong written and verbal communication skills, with the ability to tailor messaging from engineering teams to executive leadership.
Demonstrated ability to balance innovation, speed, risk management, and long-term maintainability.

Nice To Haves

Master's or Bachelor's degree in Computer Science, Engineering, Data Science, or related engineering field.
Experience working in large enterprise, platform-oriented environments with complex stakeholder ecosystems.
Proven track record migrating BI platforms from Power BI and Tableau to modern cloud-native solutions like Databricks.
Experience building Text-to-SQL agents using Databricks Genie or similar agentic AI platforms.
Familiarity with cloud AI platforms and services, including vector search, AI gateways, and observability frameworks.
Experience helping engineering organizations adopt AI-powered development tools and data engineering practices.
Track record of mentoring architects, engineers or leading architecture communities of practice.

Responsibilities

Establish the strategic direction for JLL's AI/BI ecosystem, defining how semantic and context layers will unlock new AI-driven data consumption capabilities.
Evangelize consistent methodologies that drive business line adoption of new consumption patterns.
Partner with product, platform, and data engineering teams across JLL to guide initiatives and drive architectural adoption.
Partner with business units, product leaders, and engineering teams to shape data layers for AI-first consumption and modernize analytics strategies across the organization.
Design and establish ontologies, knowledge graphs, and semantic models that enable intelligent data discovery and consumption.
Architect analytical data models and dimensional designs that support both traditional analytics and AI-driven use cases.
Lead cloud-native data architecture initiatives leveraging Databricks technology stack on Azure or AWS.
Build and deploy AI-first data consumption solutions through MCP and Text-to-SQL agent implementations using Databricks Genie or JLL-built SQL query agents.
Drive architecture for agentic AI capabilities and intelligent data consumption use cases, implementing rigorous evaluation frameworks to ensure consistency and reliability at scale.
Design and build agentic solutions that integrate unstructured data through RAG agents and structured data through SQL query agents.
Mentor technical leads and senior engineers, raising the technical bar and fostering architectural excellence across the organization.
Lead architecture reviews, technical strategy discussions, and investment decisions related to the data platform.
Champion AI-Harness adoption, enabling engineering teams to leverage AI-powered development lifecycle capabilities for building modern consumption patterns.