Director, Data Engineering

JLL•Chicago, IL

22h•Remote

About The Position

The Director of Data Engineering, Platform is a key technical leadership role responsible for building, leading, and mentoring the team that designs, builds, and operates JLL's core enterprise data platform. This leader will own the technical strategy and execution for our foundational data infrastructure, including data ingestion, streaming pipelines, data lake/warehouse, and data processing frameworks. This position is critical to JLL's Data and AI strategy, providing the scalable, reliable, and secure data backbone required to power advanced analytics, AI/ML innovation, and data-driven products across the enterprise. The Director will ensure the platform is built for self-service, enabling capabilities for the Business, Data Science, Analytics, and Application Engineering teams to leverage data with speed and confidence. This role requires a proven engineering leader with deep technical expertise in modern data architecture, a passion for building high-performing teams, and the ability to partner effectively with stakeholders across the organization to deliver enterprise-scale data solutions.

Requirements

Bachelor’s degree in computer science, Engineering, or a related technical field.
10+ years of hands-on experience in data engineering, software engineering, or related fields.
5+ years of formal experience in a people management role, leading and mentoring engineering teams.
Proven experience designing, building, and operating large-scale, cloud-native data platforms (AWS, GCP, or Azure).
Expert-level knowledge of modern data architecture patterns and big data technologies (e.g., Spark, Kafka, Flink, Airflow).
Deep experience with modern unified data platforms like Databricks, and cloud data warehouses (e.g., Snowflake, Big Query, Redshift), with a strong understanding of Lakehouse architecture.
Strong programming skills in at least one language, such as Python, Scala, or Java.

Nice To Haves

Master's Degree or other advanced degree in a relevant technical field.
Experience leading geographically distributed or global engineering teams.
Experience with containerization (Docker, Kubernetes) and Infrastructure as Code (Terraform).
Knowledge of the real estate technology (Prop Tech) domain or enterprise B2B software environments.
People Leadership: A dedicated and empathetic leader with a proven ability to build, motivate, and develop high-performing engineering teams.
Technical Vision: The ability to define a long-term technical strategy and inspire a team to execute it.
Architectural Expertise: Deep, hands-on knowledge of modern, distributed data systems and cloud infrastructure.
Execution Focus: A strong bias for action and the ability to drive projects to completion in a fast-paced, agile environment.
Stakeholder Management: Excellent communication and interpersonal skills, with the ability to build strong relationships and influence stakeholders at all levels.
Problem Solving: Strong analytical and critical thinking skills with the ability to navigate ambiguity and solve complex technical challenges.
Business Acumen: The ability to understand business needs and translate them into technical requirements and platform capabilities.

Responsibilities

Team Leadership & Platform Development Build, lead, mentor, and inspire a high-performing, globally distributed data platform team.
Define and execute the technical strategy and roadmap for the enterprise data platform, overseeing the end-to-end development lifecycle from architecture to deployment and operations.
Manage hiring, performance, career development, and resource allocation to ensure the team delivers its commitments with excellence.
Champion agile methodologies, a DevOps mindset, and a culture of operational excellence, defining and monitoring SLOs for all platform services.
Data Governance, Quality & MDM Enablement Partner with the central Data Governance team to implement technical solutions that enforce data policies, standards, and compliance requirements across the platform.
Build platform capabilities for data lineage, metadata management, and data quality monitoring to empower data stewards and ensure data is trusted and well-understood.
Architect and implement robust data security controls, including role-based access (RBAC), encryption, and data masking frameworks to protect sensitive information.
Analytics & Insight Enablement Develop the scalable, foundational data services and self-service tools that empower Data Science and Analytics teams to work efficiently.
Build a performant and reliable platform capable of supporting the entire analytics lifecycle, from historical reporting to predictive modeling and automated decisioning.
Engineer performant and reliable data pipelines that provide clean, structured, and well-documented datasets for consumption by downstream analytics and product teams.
Cross-Functional Collaboration Partner closely with key stakeholders in Data Science, Analytics, Product Management, and Application Engineering to understand their needs and ensure the data platform meets their requirements.
Collaborate with Product and Application teams to provide the data APIs and services needed to embed data insights into digital platform experiences.
Act as a key technical advisor and evangelist for the data platform, driving adoption and ensuring its capabilities are well understood across the organization.
Ensure alignment of platform investments and roadmaps with enterprise priorities through transparent communication and stakeholder management.