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Chicago, Illinois, United States
Hybrid
Not Available
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.
Sr. Director, Data Engineering (REMS)
About JLL and JLL Technologies
JLL is a leading professional services firm that specializes in real estate and investment management. Our vision is to reimagine the world of real estate, creating rewarding opportunities and amazing spaces where people can achieve their ambitions. In doing so, we will build a better tomorrow for our clients, our people, and our communities.
JLL Technologies is a specialized group within JLL. At JLL Technologies, our mission is to bring technological innovation to commercial real estate. We deliver unparalleled digital advisory, implementation, and services solutions to organizations globally. Our goal is to leverage technology to increase the value and liquidity of the world's buildings, while enhancing the productivity and happiness of those that occupy them.
What this job involves
We are seeking an experienced Sr. Director, Data Engineering to lead the REMS (Real Estate Management Services) Data Engineering team within JLL Technologies. In this role, you will own people leadership, delivery, and technical direction for the data platforms and pipelines that power REMS products across JLL's global real estate management operations — spanning property and lease data, facilities workflows, work order management, and operational intelligence.
You will set priorities in close partnership with REMS Product and Engineering leadership, govern the technical roadmap, grow a high-performing team, and ensure the delivery of reliable, well-governed data assets that scale with the business. The scope spans platform strategy, data architecture, team development, and stakeholder alignment across REMS and enterprise data functions.
The ideal candidate blends Principal Data Engineer-level technical credibility — expert data engineering, cloud architecture, and cross-domain platform delivery — with proven experience managing through leads and managers, navigating complex enterprise environments, and translating real estate management data challenges into durable engineering capabilities.
Location: Chicago or Dallas
Travel 20%
What you'll get to do
As Director of Data Engineering for REMS, your "customers" include REMS Product leadership, application and platform engineering teams, facilities and property operations practitioners who depend on accurate and timely data, and enterprise data consumers across JLL. Your mission is to lead the REMS Data Engineering function — defining the roadmap, operating model, team structure, and engineering standards that turn complex real estate management data into trusted, scalable platform capabilities.
This is an opportunity to shape how data engineering enables the next generation of REMS products — from intelligent property workflows and lease analytics to data-driven operational automation — while building the engineering culture, governance practices, and technical foundations that make that platform sustainable and trusted across JLL.
Key responsibilities
Strategic architecture and vision: Define and drive the REMS data platform strategy, consolidating fragmented data sources and legacy pipelines into a unified, governed, and scalable architecture that serves as the foundation for analytics, AI, and operational decision-making across real estate management.
Technical leadership: Provide hands-on technical leadership across the REMS Data Engineering team and related initiatives — setting architectural standards, design patterns, and engineering best practices that raise the quality bar across the organization and ensure alignment with enterprise platform standards.
Data platform delivery: Oversee the design, delivery, and continuous improvement of REMS data pipelines, APIs, and backend data services that ingest, transform, and serve property, lease, facilities, and operational data to downstream products, analytics, and AI systems.
Data modeling and architecture: Own data modeling standards across REMS — including relational, dimensional, and NoSQL schemas — ensuring data structures are designed for performance, maintainability, and reliable consumption by business intelligence, data science, and application teams.
Data governance and quality: Establish DataOps practices, data quality frameworks, lineage tracking, and compliance controls that ensure REMS data products are production-ready, auditable, and trusted — with clear ownership models and monitoring across all data assets.
Enterprise integration and API strategy: Architect integration patterns and API strategies that enable seamless data access across REMS applications, analytics platforms, and enterprise systems — including event-driven patterns and consumption standards for both internal and external data consumers.
Cross-functional leadership: Partner with REMS Product, Application Engineering, Enterprise Data, and business stakeholders to align data platform capabilities with product strategy and operational priorities — translating complex data challenges into actionable roadmaps with measurable outcomes.
Team development and mentorship: Hire, develop, and retain data engineers and team leads across all levels; conduct architecture and delivery reviews, provide technical guidance, and build a team culture defined by ownership, curiosity, and continuous improvement.
Stakeholder management: Serve as the data engineering voice in product reviews, architecture forums, and executive presentations — communicating roadmap, trade-offs, and technical direction with clarity and confidence to both technical and business audiences.
Who you are
You are a people leader who still speaks fluent data engineering — pipelines, platforms, data models, and the unglamorous work of making real estate management data trustworthy at scale. You are genuinely curious about the "why" and the "what" behind every data problem, not just the "how," and you bring that curiosity into discovery conversations with REMS product and operations stakeholders before ever reaching for a technical solution. You are as comfortable in an architecture review with senior engineers as you are in a roadmap discussion with product executives, and you build trust in both rooms by listening well and delivering reliably. You create clarity for your team when priorities compete, and you develop managers and engineers who grow in scope, confidence, and impact.
Required qualifications
People management: 5+ years of people management experience, including at least 1–2 years managing managers or team leads — not just ICs — with accountability for performance, staffing, delivery outcomes, and team development across multiple scrum teams.
10+ years of data engineering experience across multiple large, complex projects and technology domains.
Expert proficiency in Python and SQL; strong distributed data processing experience with PySpark/Spark; demonstrated ability to architect complex end-to-end data solutions.
5+ years hands-on with cloud platforms (Azure or AWS), including advanced data services such as Databricks, Azure Data Factory, Synapse, AWS Glue, or Redshift.
Proven data modeling expertise across relational, dimensional, and NoSQL schemas (CosmosDB, MongoDB, PostgreSQL); experience designing data structures that balance performance, scalability, and analytical consumption.
Demonstrated experience establishing data governance frameworks in a production enterprise environment — data quality standards, lineage tracking, ownership models, and compliance controls.
Experience orchestrating multiple data engineering project teams simultaneously; track record of shaping organizational data strategy and aligning engineering priorities with business outcomes.
Exceptional communication and stakeholder management skills — able to earn trust quickly, drive alignment across product and engineering, and present technical trade-offs clearly to executive audiences.
Preferred qualifications
Experience leading data engineering for a real estate, facilities, lease management, or asset-intensive operational domain.
Familiarity with REMS or related property management platforms (e.g., MRI, Yardi, IBM Maximo, ServiceNow FM).
Hands-on experience with agentic AI, RAG architectures, vector databases, or MCP integrations for building AI-ready data foundations.
Experience with data orchestration tools such as Airflow, Prefect, or dbt for managing complex pipeline dependencies and transformations.
Strong DevOps and DataOps practices — CI/CD pipeline design, containerization (Docker, Kubernetes), infrastructure-as-code (Terraform or CloudFormation), and observability tooling.
Experience with data governance compliance standards (GDPR, CCPA, data residency requirements) and enterprise security practices for sensitive data.
Master's degree in Computer Science, Engineering, Data Science, or a related field.
Key attributes
Leadership: Builds and retains strong teams through leads and managers; delegates effectively while staying close to critical technical risks and maintaining the engineering credibility that earns team respect.
Stakeholder Partnership: Navigates REMS product and enterprise priorities with poise; negotiates scope and timelines with data-driven rationale and a consistent bias toward shared outcomes.
Judgment: Makes sound trade-offs among quality, speed, cost, and risk — especially in domains where data accuracy has direct operational, financial, or contractual consequences.
Communication: Explains technical architecture and platform trade-offs clearly to executives and product partners; listens actively for the business constraints that should shape engineering decisions.
Ownership: Accountable for team outcomes, platform health, and the continuous improvement of engineering practices — not just delivery milestones.
This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.
Expected compensation for this position:
Final compensation packages are determined by various considerations including but not limited to candidate qualifications, location, market conditions, and internal considerations.
Location:
On-site –Chicago, IL, Dallas, TXIf this job description resonates with you, we encourage you to apply, even if you don’t meet all the requirements. We’re interested in getting to know you and what you bring to the table!
Personalized benefits that support personal well-being and growth:
JLL recognizes the impact that the workplace can have on your wellness, so we offer a supportive culture and comprehensive benefits package that prioritizes mental, physical and emotional health. Some of these benefits include:
At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.
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