Senior Manager, Data Engineering
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Key skills for this role
About the Role
JLL is seeking a Senior Manager, Data Engineering to lead the Enterprise Platform Data Engineering team. You will drive people leadership, delivery excellence, and technical direction for data platforms and pipelines.
Key Skills for This Role
Responsibilities
- Lead and mentor a team of data engineers, providing technical guidance, performance management, and career development
- Define and execute the Enterprise Platform Data Engineering roadmap, aligning team priorities with JLL's enterprise data strategy
- Architect and oversee enterprise scale data platforms and pipelines that consolidate siloed data sources into unified, governed, and scalable foundations
- Partner with cross functional stakeholders to deliver trusted data capabilities that enable advanced analytics, semantic layers, and intelligent data discovery
- Establish and drive DataOps best practices, including CI/CD pipelines, data quality frameworks, observability, lineage tracking, and compliance controls
- Guide technical architecture reviews, technology evaluations, and proof of concept initiatives
- Serve as the data engineering voice in executive forums, communicating roadmaps, trade offs, and strategic direction
Requirements
- 3+ years of direct people management experience leading data engineers or equivalent technical teams
- 10+ years of experience in data engineering and Big Data development
- 5+ years of hands on experience with cloud platforms (Azure or AWS)
- Expert level proficiency in multiple server side programming languages (Python, Java, Scala)
- Proven expertise in data modeling, data architecture, and designing scalable data systems
- Deep understanding of machine learning lifecycle, MLOps practices, model governance, and production ML systems
- Extensive experience with diverse data technologies including SQL databases, NoSQL databases, and AI centric databases
Full Job Posting
What this job involves
- We are seeking an experienced Senior Manager, Data Engineering, to lead the Enterprise Platform Data Engineering team at JLL Technologies.
- You will drive people leadership, delivery excellence, and technical direction for data platforms and pipelines that power JLL's enterprise data strategy.
- This is an opportunity to shape how data engineering enables data governance, master data management, and enterprise wide data discoverability.
What your day to day will look like
- Lead and mentor a team of data engineers, providing technical guidance, performance management, and career development.
- Define and execute the Enterprise Platform Data Engineering roadmap, aligning team priorities with JLL's enterprise data strategy.
- Architect and oversee enterprise scale data platforms and pipelines that consolidate siloed data sources into unified, governed, and scalable foundations.
- Partner with cross functional stakeholders to deliver trusted data capabilities that enable advanced analytics, semantic layers, and intelligent data discovery.
- Establish and drive DataOps best practices, including CI/CD pipelines, data quality frameworks, observability, lineage tracking, and compliance controls.
- Guide technical architecture reviews, technology evaluations, and proof of concept initiatives.
- Serve as the data engineering voice in executive forums, communicating roadmaps, trade offs, and strategic direction.
Required Qualifications
- 3+ years of direct people management experience leading data engineers or equivalent technical teams.
- 10+ years of experience in data engineering and Big Data development.
- 5+ years of hands on experience with cloud platforms (Azure or AWS).
- Expert level proficiency in multiple server side programming languages (Python, Java, Scala).
- Proven expertise in data modeling, data architecture, and designing scalable data systems.
- Deep understanding of machine learning lifecycle, MLOps practices, model governance, and production ML systems.
- Extensive experience with diverse data technologies including SQL databases, NoSQL databases, and AI centric databases.
Preferred Qualifications
- Master's degree in Computer Science, Engineering, Data Science, or a related field.
- Deep expertise designing and implementing semantic layers, ontologies, and knowledge graphs.
- Extensive experience with streaming architectures using Kafka, Spark Streaming, Flink, or similar.
- Expert level understanding of DevOps principles with hands on experience in CI/CD pipelines, infrastructure as code, and container orchestration.
- Significant experience with LLM driven workflows, RAG architectures, and orchestration frameworks.
- Experience with data governance frameworks, compliance standards (GDPR, CCPA), and enterprise security practices.
- Published technical articles, conference presentations, or contributions to open source projects.
Estimated compensation
- 185,000.00 – 230,000.00 CAD per year.
Location
- Remote – Toronto, ON
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