Principal Data Architect

JLL; Chicago (IL); On-site; USD 170,000 - 230,000; Full time

Job summary

JLL seeks a hands-on Principal Data Architect to transform data consumption and establish AI/BI practices. You will define enterprise semantic layers and context models, enabling AI-powered consumption for business lines.

You will collaborate with product and platform teams to scale solutions across the organization and champion data-driven decision making. The role requires senior leadership, hands-on implementation, and mentorship for engineers, with focus on Databricks, cloud-native data

Qualifications

• 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 or leadership roles.
• Proven experience building semantic layers and enterprise ontologies for AI-driven consumption.
• Experience with cloud-native data platforms and Databricks stack.
• Strong communication skills for executive-level storytelling.

Responsibilities

• Define strategic direction for JLL's AI/BI ecosystem and semantic/context layers.
• Design ontologies, knowledge graphs, and semantic models for intelligent data discovery.
• Architect analytical data models and dimensional designs for traditional analytics and AI use cases.
• Lead cloud-native data architecture initiatives leveraging Databricks on Azure or AWS.
• Build and deploy AI-first data consumption solutions including Text-to-SQL agents and MCP integration.
• Mentor technical leads and engineers, driving architectural excellence and governance.

Skills

Semantic modeling

Enterprise ontology

Context layer architecture

AI/BI strategy

Databricks

Azure/AWS

Text-to-SQL agents

LLM-based data apps

Data platform consumption

Communication with leadership

Education

Bachelor's or Master's in CS/Engineering

Tools

Databricks

Apache Spark

DBT

Job description

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.

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).

Core Responsibilities

• Strategic Vision: Establish the strategic direction for JLL's AI/BI ecosystem, defining how semantic and context layers will unlock new AI-driven data consumption capabilities.
• Data Consumption Standards and Patterns: Evangelize consistent methodologies that drive business line adoption of new consumption patterns
• Cross-Functional Collaboration: Partner with product, platform, and data engineering teams across JLL to guide initiatives and drive architectural adoption.

Key Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.

What Success Looks Like

• Business units have a trusted architecture partner who guides AI-first data consumption strategies and platform decisions with clear technical leadership.
• The organization operates with well-defined standards and reusable patterns for data solutions, supported by measurable success metrics and KPIs.
• A consistent, governed practice exists for building semantic and context layers across all business lines, enabling scalable AI-driven consumption.
• AI-native data consumption solutions are optimized for speed, cost-efficiency, and engineering excellence
• Engineering teams effectively leverage AI-powered development lifecycle capabilities to accelerate delivery while maintaining quality and governance standards.

Leadership Expectations

• This role operates as a senior technical leader across organizational boundaries. The Principal Data Architect will shape strategic direction for AI and analytics initiatives, drive critical architectural decisions, mentor technical teams, and establish enterprise-wide standards for data architecture practices at JLL.