Senior Manager, Data Engineering

Jones Lang LaSalle Incorporated; Chicago (IL); On-site; USD 163,000 - 199,000; Full time

Benefits offered by this job

401(k) plan with matching

Comprehensive Medical, Dental & Vision

Paid parental leave

Paid Time Off and Holidays

Daily Pay

Job summary

Jones Lang LaSalle Incorporated is seeking an experienced Senior Data Engineering Manager to lead multiple scrum teams responsible for Corporate Functions data. You will shape the data roadmap, ensure quality and governance, and drive reliable streaming and batch pipelines across Azure and Spark ecosystems.

You will partner with product, analytics, and business leaders to translate needs into scalable data products, while mentoring engineers and promoting a high‑performing, inclusive culture.

Qualifications

• Leadership experience managing data engineers or tech ICs; setting priorities and coaching teams.
• 7+ years in data engineering with end-to-end delivery of large projects.
• Strong Python/SQL, Azure data services, and distributed processing experience.
• Hands-on with streaming technologies (Kafka/Spark Streaming) and data pipelines.
• Knowledge of data governance, quality, lineage, metadata, and security practices.
• Ability to deliver through agile teams and manage multiple workstreams.

Responsibilities

• Lead batch and streaming data pipelines on Azure, Python, Spark.
• Direct real-time data delivery and ensure latency and reliability for downstream consumers.
• Own data governance, quality, lineage, cataloging, and automation across data domains.
• Manage delivery priorities, tech debt, and operational demands across teams.
• Align roadmaps with Enterprise Data Platform standards and modernization efforts.
• Establish CI/CD, observability, and incident response for data pipelines.
• Collaborate with product, analytics, security, and governance teams to deliver end-to-end solutions.
• Coach and develop engineers and tech leads; foster inclusion and growth.
• Communicate status and risks clearly to stakeholders; optimize for business value.

Skills

People management

Data engineering

Python & SQL

Azure data services

Streaming pipelines

Data governance & quality

Delivery management

Cross-functional collaboration

Communication

Education

Bachelor’s or Master’s in CS/Engineering or related

Tools

CosmosDB

MongoDB

NoSQL databases

CI/CD

Infrastructure as code

Job description

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. 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. The Data Engineering team builds and operates the data products and pipelines that power JLL’s Corporate Functions, including areas such as finance, HR, Legal, Compliance and shared services. Working on the Enterprise Data Platform (EDP), we turn internal enterprise data into trusted, governed, and increasingly real‑time assets that leaders and teams across the firm rely on for reporting, planning, and operational decisions.

We help our people thrive, grow meaningful careers and find a place where they belong.

What this job involves

As Senior Data Engineering Manager, you will lead multiple related scrum teams of data engineers responsible for Corporate Functions data – from ingestion and streaming pipelines through curated, governed data products. Your teams own the reliability, quality, and timeliness of the data that underpins enterprise reporting, financial and workforce analytics, and shared‑services operations. You will own delivery and direction for the Corporate Functions data engineering function: setting priorities across teams, allocating resources, guiding technical design, and partnering with product, analytics, and business leaders to translate needs into a clear roadmap. You will be accountable for team outcomes, data quality standards, and the continuous improvement of engineering practices. The ideal candidate blends the technical credibility of a Lead Data Engineer – hands‑on depth in Python, Azure, and streaming architectures – with proven people leadership, and the ability to build trust with senior business stakeholders.

What you’ll get to do

As Senior Data Engineering Manager, your “customers” include leaders and teams in Finance, HR, Legal, Compliance and other Corporate Functions, data analysts and BI teams, product managers, and fellow platform and governance teams across JLL Technologies. Your mission is to lead the Corporate Functions data engineering function – defining the roadmap, operating model, and quality standards that make data trusted, timely, and reusable. This is an opportunity to shape how streaming and governed data enable faster, better-informed decisions across the enterprise – and to grow a high‑performing engineering organization while doing it.

Key responsibilities

• Technical Leadership: Provide hands‑on technical direction for batch and streaming data pipelines built on Azure, Python, and Spark. Guide architecture and design reviews, set engineering standards for reusable frameworks, and stay close to critical technical risks.
• Real‑Time and Streaming Data Delivery: Lead the design and operation of event‑driven pipelines using technologies such as Kafka and Spark Streaming, so that financial, workforce, and operational data reaches downstream consumers with the latency and reliability the business requires.
• Data Governance and Quality: Own data quality, lineage, cataloging, and stewardship practices for Corporate Functions data domains, including sensitive finance and HR data. Define measurable quality standards, automate validation and monitoring in pipelines, and partner with enterprise governance and security teams to ensure compliance with JLL data policies and access controls.
• Delivery Management: Set priorities and manage execution across multiple scrum teams. Balance roadmap commitments, technical debt, and operational demands; maintain predictable delivery; and adapt plans as business needs evolve.
• Platform Alignment and Modernization: Align team deliverables with the Enterprise Data Platform strategy. Drive adoption of platform standards, ingestion patterns, and cloud‑native services, and contribute to modernization of legacy data assets.
• Reliability and Operational Excellence: Establish CI/CD, observability, and incident management practices that keep pipelines healthy. Ensure teams meet service‑level expectations and learn from production issues through blameless reviews.
• Cross‑Functional Leadership: Collaborate with product, analytics, data science, platform, security, and governance teams to deliver end‑to‑end data solutions. Resolve dependencies, negotiate shared priorities, and keep teams aligned on outcomes.
• Team Development and Mentorship: Recruit, coach, and retain strong engineers and team leads. Set clear expectations, provide regular feedback, build career growth paths, and foster a culture of inclusion, ownership, and continuous learning.
• Stakeholder Management: Build trusted relationships with Corporate Functions business and technology leaders. Communicate status, risks, and trade‑offs clearly, manage expectations on scope and timelines, and ensure engineering work maps to business value.
• Resource and Budget Planning: Partner with leadership on headcount, vendor, and cloud cost planning for your teams, optimizing talent utilization and cost efficiency across products and initiatives.

Who you are

You are a people‑first engineering leader who has grown from strong hands‑on data engineering roots. You earn credibility with engineers by understanding the technical detail – from distributed processing to data modeling trade‑offs – while inspiring them through clear direction, coaching, and high standards. You navigate competing priorities with composure, explain complex topics plainly to executives, and hold yourself accountable for both team outcomes and the quality of the data your teams deliver. You are energized by turning ambiguous business needs into reliable, governed data products.

Required Qualifications

• People management: 2+ years directly managing data engineers or technical individual contributors; experience setting priorities, allocating work, and coaching teams; managing managers is not required.
• Data engineering experience: 7+ years in data engineering, including multiple large and complex projects delivered end to end.
• Technical depth: Advanced Python and SQL; strong experience with Azure data services and distributed processing (e.g., Spark/PySpark); experience building reusable frameworks.
• Streaming: Hands‑on experience designing or leading real‑time data pipelines with Kafka, Spark Streaming, or equivalent technologies.
• Data governance and quality: Working knowledge of data quality frameworks, lineage, metadata management, and data governance practices.
• Delivery: Experience managing or training teams of data engineers and setting priorities across multiple data engineering workstreams in an agile environment.
• Communication: Strong written and verbal communication skills, with the ability to engage both technical and business stakeholders.

Preferred qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with corporate data domains such as finance, HR, or shared services (e.g., ERP, HRIS, or enterprise reporting data), or in commercial real estate.
• Experience with NoSQL, graph, or multi‑model databases (e.g., CosmosDB, MongoDB) and complex cross‑system integrations.
• Familiarity with data cataloging and governance tooling, and with CI/CD and infrastructure‑as‑code practices.
• Experience with modern lakehouse or data platform architectures and enterprise data platforms.
• Exposure to applying AI/ML or LLM‑based capabilities to data engineering and data quality workflows.

Key attributes

• Leadership: Builds and retains strong teams; delegates effectively while staying close to critical technical risks.
• Stakeholder Partnership: Navigates competing priorities with poise; negotiates scope and timelines with data‑driven rationale.
• Judgment: Makes sound trade‑offs among quality, speed, cost, and risk.
• Communication: Explains technical concepts clearly to executives; listens for business constraints that should shape engineering decisions.
• Ownership: Accountable for team outcomes, platform health, and continuous improvement of engineering practices.

This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.

Expected compensation for this position: 162,700.00 – 199,300.00 USD per year 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

Personalized benefits that support personal well‑being and growth:

• 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

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 endeavor 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 [e-mail]. 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.

For further information, visit jll.com.