Data Developer

JLL•Toronto, ON

10d•CA$120,000 - CA$140,000•Hybrid

About The Position

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. What this job involves: As a Data Developer in JLLT, you will utilize AI, automation, and domain expertise to develop enterprise data solutions that drive strategic business value. You’ll translate business needs into technical requirements while demonstrating strategic awareness of how data engineering supports organizational objectives. Working with intermediate to advanced technical skills, you’ll solve medium to high complexity data problems and collaborate with senior engineers on strategy execution. This role focuses on building production-ready data pipelines, expanding CI/CD capabilities, and delivering solutions that impact scrum team deliverables while communicating effectively with cross-functional stakeholders. This role has flexibility to work remotely at times and candidates may be required to work outside of standard business hours on occasion to support global employees and times zones.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Mathematics, Statistics, or related quantitative discipline
3+ years of experience in data engineering, data development, or related technical field
Proven experience building ETL/data pipelines in production environments
Experience with agile development methodologies and cross-functional teams
Intermediate Python skills including decorators, generators, object-oriented programming
Solid SQL proficiency with query optimization and performance tuning experience
Experience with data orchestration platforms (Airflow, Azure Data Factory, SSIS, or similar)
Familiarity with Apache Spark, PySpark, or similar distributed processing frameworks
Hands-on experience with Azure, AWS, or GCP data services (Databricks, Azure Functions, Delta Lake, etc.)
Familiarity with semantic layer tools (CubeJS or similar) for data access and analytics
Understanding of continuous integration/deployment for data pipelines
Knowledge of software design patterns and their application in data engineering
Basic understanding of AI/automation tools and their integration into data workflows

Nice To Haves

Candidates may be required to work outside of standard business hours on occasion to support global employees and times zones.

Responsibilities

Design and implement complete ETL/ELT workflows using intermediate to advanced techniques
Build and modify CI/CD pipelines for data processing workflows
Develop native data ingestion capabilities from various sources (APIs, databases, file systems)
Implement data validation, error handling, and monitoring in production pipelines
Incorporate AI and automation patterns into data engineering solutions
Develop solutions that leverage automation for improved efficiency and scalability
Apply intermediate Python techniques including decorators, generators, and design patterns
Build reusable components and frameworks for team use
Translate business requirements into technical data engineering solutions
Collaborate with product managers, analysts, and other stakeholders on data needs
Participate actively in scrum/agile development processes
Provide technical expertise to support strategic decision-making
Apply data modeling principles and data warehousing concepts
Design database schemas and data integration patterns
Work with cloud services (Azure/AWS/GCP) for scalable data solutions
Optimize data storage and retrieval for performance and cost