Senior Data Engineer

Jones Lang LaSalle Americas, Inc.

Forward Deployed Data Engineer creating and delivering data-driven solutions for JLL. Collaborating with product, program, and engineering teams to tackle high-priority business problems.

Posted 5/29/2026full-timeChicago • Illinois • 🇺🇸 United StatesSenior💰 $140,000 - $180,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformNoSQLPythonSQL

About the role

Key responsibilities & impact

Drive 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
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
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
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
Embed directly with product, program, and engineering teams to co-define problems and co-deliver solutions
Contribute to technical direction and help build alignment across teams through strong communication and collaboration
Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in presentations
Support and mentor 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.

Requirements

What you’ll need

4+ years of professional software or data engineering experience, including hands-on solution design and architecture contributions
Experience designing and delivering 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.

Benefits

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

solution designarchitecturedata engineeringAI systemsdata pipelinesETLELTSQLNoSQLPython

Soft Skills

communicationinterpersonal skillscollaborationproblem-solvingcuriositymentorshiptrust-buildingadaptabilityalignmentteam culture