
10,000+ employees
🏠 Real Estate
🤝 B2B
💼 Consulting
Real Estate • B2B • Consulting
Jones Lang LaSalle Americas, Inc. is a company that provides commercial real estate services for corporations and investors worldwide. Their focus is on helping clients save money, increase productivity, and improve sustainability in real estate operations.
🕒 Yesterday
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10,000+ employees
🏠 Real Estate
🤝 B2B
💼 Consulting
Real Estate • B2B • Consulting
Jones Lang LaSalle Americas, Inc. is a company that provides commercial real estate services for corporations and investors worldwide. Their focus is on helping clients save money, increase productivity, and improve sustainability in real estate operations.
• Establish the strategic direction for JLL's AI/BI ecosystem and define how semantic and context layers unlock AI-driven data consumption capabilities • Evangelize consistent data consumption methodologies that drive business line adoption • Partner with product, platform, data engineering, business unit, and engineering teams across JLL • Shape data layers for AI-first consumption and modernize analytics strategies • Design and establish ontologies, knowledge graphs, and semantic models • Architect analytical data models and dimensional designs for traditional analytics and AI-driven use cases • Lead cloud-native data architecture initiatives using the 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 • Implement evaluation frameworks to ensure consistency and reliability at scale • Design and build agentic solutions integrating unstructured data through RAG agents and structured data through SQL query agents • Mentor technical leads and senior engineers • Lead architecture reviews, technical strategy discussions, and data platform investment decisions • Champion AI-Harness adoption for AI-powered development lifecycle capabilities • Establish enterprise-wide standards, reusable patterns, technical guardrails, and measurable success metrics
• 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 • 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 • Candidates must be authorized to work in the United States without sponsorship
• 401(k) plan with matching company contributions • Comprehensive Medical, Dental & Vision Care • Paid parental leave at 100% of salary • Paid Time Off and Company Holidays • Early access to earned wages through Daily Pay • Supportive culture prioritizing mental, physical and emotional health • Reasonable accommodations for individuals with disabilities
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