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Senior Manager, Data Engineering

Job in Chicago, Cook County, Illinois, 60290, USA
Listing for: JLL
Full Time position
Listed on 2026-10-16
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 150000 - 210000 USD Yearly USD 150000.00 210000.00 YEAR
Job Description & How to Apply Below

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.

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…
Position Requirements
10+ Years work experience
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