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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.
Job Responsibility:
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.
Manage hiring, performance, career development, and resource allocation.
Champion agile methodologies, a DevOps mindset, and a culture of operational excellence.
Partner with the central Data Governance team to implement technical solutions that enforce data policies.
Build platform capabilities for data lineage, metadata management, and data quality monitoring.
Architect and implement robust data security controls.
Develop the scalable, foundational data services and self-service tools that empower Data Science and Analytics teams.
Build a performant and reliable platform capable of supporting the entire analytics lifecycle.
Engineer performant and reliable data pipelines.
Partner closely with key stakeholders in Data Science, Analytics, Product Management, and Application Engineering.
Collaborate with Product and Application teams to provide the data APIs and services.
Act as a key technical advisor and evangelist for the data platform.
Ensure alignment of platform investments and roadmaps with enterprise priorities.
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.
Candidates must be authorized to work in the United States without sponsorship.
Nice to have:
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.