{"id":180660,"url":"https://alion.io/job/jones-lang-lasalle-staff-data-engineer-2","title":"Staff Data Engineer","company":{"id":616,"name":"Jones Lang LaSalle","domain":"jll.com","url":"https://alion.io/company/jones-lang-lasalle","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":493,"ghost_share":0.004,"stale_share":0.087,"repost_share":0.039,"time_to_fill_p50_days":7,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Chicago, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Arize Phoenix","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"dbt","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prefect","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Weaviate","optional":false},{"name":"Weights & Biases","optional":false},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-08-31T16:42:07Z","employer_posted_date":"2026-08-31","last_verified_at":"2026-10-25T13:20:12Z","board_verified":true,"closed_at":null,"days_open":55,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":55},"description":"JLL empowers you to shape a brighter way.\nOur 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.\nAbout JLL and Data Engineering\nJLL 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.\nThe 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.\nRole Overview\nAs 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.\nYou 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.\nKey Responsibilities\nSolution Design & Architecture\nLead solution design for complex, cross-functional data and AI problems - from initial discovery through to technical blueprint\nDefine and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences\nDesign scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability\nParticipate in architecture reviews and Critical Design Reviews (CDRs), ensuring alignment with enterprise patterns and platform standards\nCreate clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs\nRapid Prototyping & Solution Delivery\nDesign and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks\nBring genuine curiosity to every engagement - deeply understanding the business case, problem context, and constraints before converging on a solution\nBalance speed of delivery with enterprise standards - your prototypes are production-ready, not throwaway\nContinuously iterate on solutions based on direct feedback from product managers, program leads, and end users\nAI Agent Development & Agentic Systems\nDesign, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end\nDevelop and maintain agent skills - discrete, reusable capabilities that compose into larger agentic pipelines\nImplement and extend MCP (Model Context Protocol) servers and clients to connect AI agents with enterprise tools, APIs, and data sources\nBuild agent orchestration layers using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel\nDesign evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production\nStay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team\nAI & Data Engineering\nBuild and deploy AI-powered features and pipelines that automate workflows, surface insights, and enhance decision-making\nDesign and implement scalable data pipelines, APIs, and backend services that serve both internal tools and customer-facing products\nIntegrate LLMs, RAG systems, and ML models into production data workflows\nOwn data modeling, transformation, and quality across the solutions you deliver\nCollaboration & Stakeholder Engagement\nEmbed directly with product, program, and engineering teams to co-define problems and co-deliver solutions\nInfluence technical direction and build alignment across teams without relying on formal authority\nCommunicate complex technical concepts clearly to non-technical business stakeholders - in writing, in meetings, and in executive presentations\nMentor and elevate junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery\nFoster a collaborative, low-ego team culture where speed and quality go hand in hand\nQualifications\nRequired\n6+ years of professional software or data engineering experience, including solution design and architecture ownership\nDemonstrated ability to architect end-to-end data and AI systems - from requirements through deployment - with clear documentation and stakeholder communication\nHands-on experience building AI agents, including defining agent skills, tool use, memory, and multi-step reasoning\nWorking knowledge of MCP (Model Context Protocol) - including building or consuming MCP servers to connect agents with external systems\nExperience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel\nStrong hands-on experience with data engineering: pipelines, ETL/ELT, data modeling, SQL and NoSQL databases\nProficiency in Python\nExperience with cloud platforms (AWS, Azure, or GCP) and modern data stack tooling\nExceptional communication and interpersonal skills - you can earn trust quickly, navigate ambiguity, and drive alignment across diverse teams\nComfort working in fast-paced environments with shifting priorities and high ownership expectations\nPreferred\nExperience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), semantic search, and building indexing systems and data processing pipelines\nFamiliarity with prompt engineering, fine-tuning, and LLM evaluation techniques\nExperience with agent observability and tracing tools (LangSmith, Arize, Weights & Biases, or similar)\nExperience with AWS AgentCore - building, deploying, and operating agents on the platform\nKnowledge of data orchestration tools (Airflow, Prefect, or dbt)\nExperience with containerization and CI/CD practices (Docker, Kubernetes, GitHub Actions)\nBackground in real estate, financial services, or other data-intensive enterprise domains\nExperience facilitating technical discovery workshops, design sprints, or architecture reviews\nContributions to open-source agentic or data projects, or a portfolio demonstrating rapid, creative problem-solving\nThis position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.\nEstimated compensation for this position:\n160,000.00 - 200,000.00 USD per yearThis 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.\nLocation:\nOn-site -Chicago, IL, Westmont, ILIf 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!\n Personalized benefits that support personal well-being and growth:\nJLL 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:\n401(k) plan with matching company contributions\n\nComprehensive Medical, Dental & Vision Care\n\nPaid parental leave at 100% of salary\n\nPaid Time Off and Company Holidays\n\nEarly access to earned wages through Daily Pay\n\nAt 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.\nJLL Privacy Notice\nJones 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.\nFor more information about how JLL processes your personal data, please view our Candidate Privacy Statement.\nFor additional details please see our career site pages for each country.\nFor candidates in the United States, please see a full copy of our Equal Employment Opportunity policy here.\nJones 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 . 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.\nPursuant to the Arizona Civil Rights Act, criminal convictions are not an absolute bar to employment.\nPursuant to Illinois Law, applicants are not obligated to disclose sealed or expunged records of conviction or arrest.\nPursuant 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.\nCalifornia Residents only\nIf 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.\nPursuant 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.\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.\nAccepting applications on an ongoing basis until candidate identified.","description_format":"text","description_chars":11824,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Real Estate Investment","Real Estate Brokerage","Real Estate Appraisal","Facilities Management"],"lifecycle":[{"event":"open","at":"2026-08-31T16:42:07Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 45 · green card filings: 37","filings_12m":45,"filings_prev_12m":71,"green_card_filings_12m":37,"median_offered_wage_usd":127988,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":9}],"liveness":{"score":12,"band":"cold","label":"Long shot","p_open":1,"p_active":0.416,"p_room":0.28,"age_days":54,"expected_fill_days":7,"reasons":["conf:1","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-25T05:49:26Z"},"pay":{"stated_usd_annual":200000,"is_top_pay":true},"html_url":"https://alion.io/job/jones-lang-lasalle-staff-data-engineer-2","json_url":"https://alion.io/job/jones-lang-lasalle-staff-data-engineer-2.json","meta":{"generated_at":"2026-10-26T04:44:47Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":6312,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-27T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":616},"rest":"https://alion.io/mcp/rest/get_company?id=616"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fjones-lang-lasalle-staff-data-engineer-2"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fjones-lang-lasalle-staff-data-engineer-2"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fjones-lang-lasalle-staff-data-engineer-2"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/jones-lang-lasalle-staff-data-engineer-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fjones-lang-lasalle-staff-data-engineer-2"}]}