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Staff Data Engineer

Jones Lang LaSalle · Westmont, IL · Full time

Posted Aug 31, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

This is a forward deployed role, sitting close to business users. Tell me about a time you built something because you sat with the users, not because of a ticket.

What they are checking: Whether they find the real problem by working alongside users instead of only building from written requirements.

As a staff engineer, how do you raise the technical bar of a team without becoming the bottleneck?

What they are checking: Whether they lead through standards, review and mentoring rather than doing all the hard parts themselves.

Tell me about a time you pushed back on a business request because the data couldn't honestly support it.

What they are checking: Whether they protect the integrity of the data even when it disappoints a stakeholder.

What would you do

A dashboard that executives use shows numbers that don't match finance's report. How do you track it down?

What they are checking: Whether they can trace a data discrepancy end to end and communicate clearly while it is open.

You need to ship something useful in two weeks for a business team. How do you decide what to cut?

What they are checking: Whether they can move fast while knowing which shortcuts create debt that will hurt later.

About the work

Walk me through how you'd design a pipeline that pulls property and lease data from several messy source systems into one trusted model.

What they are checking: Whether they think about ingestion, data contracts, quality checks and ownership as one design, not just code.

How do you decide between batch and streaming for a new data product?

What they are checking: Whether they choose based on what the business decision actually needs rather than on what is fashionable.

What does production-grade mean to you for a data platform? Give me the specific things you check before calling it done.

What they are checking: Whether they include testing, monitoring, lineage and recovery in their definition of done.

How have you used LLMs or intelligent solutions on top of a data platform, and what went wrong at first?

What they are checking: Whether they have real experience putting AI features on data and understand their failure modes.

How do you handle schema changes in a source system you don't own?

What they are checking: Whether they design defensively with contracts and alerts so upstream changes do not silently break downstream users.

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The full job description

As published by Jones Lang LaSalle.

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. About JLL and Data Engineering 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. The Data Engineering team at JLL sits at the intersection of technology and business impact, building the data foundations and intelligent solutions that power decisions across the enterprise. We move fast, think big, and deliver production-grade platforms that transform how JLL operates — combining deep technical expertise with a relentless focus on solving real problems for real users. Role Overview As a Forward Deployed Data Engineer, you will operate at the front lines of innovation — embedded directly with product, program, and engineering teams to rapidly design, architect, prototype, and deploy data-driven solutions that solve high-priority business problems. This is not a traditional engineering role with long delivery cycles. You will be expected to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability. You bring an exceptional combination of skills: solution design and architecture experience, deep hands-on engineering across data and AI agents, and the interpersonal skills to earn trust, drive alignment, and influence without authority. You are equally comfortable whiteboarding a system architecture with senior stakeholders and writing production code the same afternoon. You have genuine curiosity about the “why” and “what” behind every problem — not just the “how” — and you thrive in fast, ambiguous environments where creative thinking and execution speed both matter. Key Responsibilities Solution Design & Architecture • Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint • Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences • Design scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability • Participate in architecture reviews and Critical Design Reviews (CDRs), ensuring alignment with enterprise patterns and platform standards • Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs Rapid Prototyping & Solution Delivery • Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks • Bring genuine curiosity to every engagement — deeply understanding the business case, problem context, and constraints before converging on a solution • Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway • Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users AI Agent Development & Agentic Systems • Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end • Develop and maintain agent skills — discrete, reusable capabilities that compose into larger agentic pipelines • Implement and extend MCP (Model Context Protocol) servers and clients to connect AI agents with enterprise tools, APIs, and data sources • Build agent orchestration layers using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel • Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production • Stay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team AI & Data Engineering • Build and deploy AI-powered features and pipelines that automate workflows, surface insights, and enhance decision-making • Design and implement scalable data pipelines, APIs, and backend services that serve both internal tools and customer-facing products • Integrate LLMs, RAG systems, and ML models into production data workflows • Own data modeling, transformation, and quality across the solutions you deliver Collaboration & Stakeholder Engagement • Embed directly with product, program, and engineering teams to co-define problems and co-deliver solutions • Influence technical direction and build alignment across teams without relying on formal authority • Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in executive presentations • Mentor and elevate junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery • Foster a collaborative, low-ego team culture where speed and quality go hand in hand Qualifications Required • 6+ years of professional software or data engineering experience, including solution design and architecture ownership • Demonstrated ability to architect end-to-end data and AI systems — from requirements through deployment — with clear documentation and stakeholder communication • Hands-on experience building AI agents, including defining agent skills, tool use, memory, and multi-step reasoning • Working knowledge of MCP (Model Context Protocol) — including building or consuming MCP servers to connect agents with external systems • Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel • Strong hands-on experience with data engineering: pipelines, ETL/ELT, data modeling, SQL and NoSQL databases • Proficiency in Python • Experience with cloud platforms (AWS, Azure, or GCP) and modern data stack tooling • Exceptional communication and interpersonal skills — you can earn trust quickly, navigate ambiguity, and drive alignment across diverse teams • Comfort working in fast-paced environments with shifting priorities and high ownership expectations Preferred • Experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), semantic search, and building indexing systems and data processing pipelines • Familiarity with prompt engineering, fine-tuning, and LLM evaluation techniques • Experience with agent observability and tracing tools (LangSmith, Arize, Weights & Biases, or similar) • Experience with AWS AgentCore — building, deploying, and operating agents on the platform • Knowledge of data orchestration tools (Airflow, Prefect, or dbt) • Experience with containerization and CI/CD practices (Docker, Kubernetes, GitHub Actions) • Background in real estate, financial services, or other data-intensive enterprise domains • Experience facilitating technical discovery workshops, design sprints, or architecture reviews • Contributions to open-source agentic or data projects, or a portfolio demonstrating rapid, creative problem-solving This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship. Estimated compensation for this position: 160,000.00 – 200,000.00 USD per year This range is an estimate and actual compensation may differ. 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, Westmont, IL If 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 may include: • 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 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. JLL Privacy Notice Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL’s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely. For more information about how JLL processes your personal data, please view our Candidate Privacy Statement . For additional details please see our career site pages for each country. For candidates in the United States, please see a full copy of our Equal Employment Opportunity policy here . Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at HRSCLeaves@jll.com . This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL. Pursuant to the Arizona Civil Rights Act, criminal convictions are not an absolute bar to employment. Pursuant to Illinois Law, applicants are not obligated to disclose sealed or expunged records of conviction or arrest. Pursuant to Columbia, SC ordinance, this position is subject to a background check for any convictions directly related to its duties and responsibilities. Only job-related convictions will be considered and will not automatically disqualify the candidate. California Residents only If you are a California resident as defined in the California Consumer Privacy Act (CCPA) please view our Supplemental Privacy Statement which describes your rights and disclosures about your personal information. If you are viewing this on a mobile device you may want to view the CCPA version on a larger device. Pursuant to the Los Angeles Fair Chance Initiative for Hiring Ordinance, JLL will consider for employment all qualified Applicants, including those with Criminal Histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Accepting applications on an ongoing basis until candidate identified.

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