ABOUT QUADREAL PROPERTY GROUP

QuadReal Property Group is a global real estate investment, operating and development company headquartered in Vancouver, British Columbia. Its assets under management are $94 billion. From its foundation in Canada as a full-service real estate operating company, QuadReal has expanded its capabilities to invest in equity and debt in both the public and private markets. QuadReal invests directly, via programmatic partnerships and through operating platforms in which it holds an ownership interest.
QuadReal seeks to deliver strong investment returns while creating sustainable environments that bring value to the people and communities it serves. Now and for generations to come.
QuadReal: Excellence lives here.
www.quadreal.com
At QuadReal, Analytics Engineers sit at the intersection of Business, Analytics, and Data Engineering and are responsible for transforming raw data into analytics-ready datasets that power business intelligence and decision making. Speaking the language of business and technical teams, they translate data insights and analysis needs into models powered by the Enterprise Data Platform - successfully blending business acumen with technical expertise and transitioning between business strategy and data development.
The Enterprise Data & Analytics (ED&A) team is looking for an Analytics Engineer to design, implement, and document data transformation pipelines and dimensional models using dbt. You’ll help build high-quality, tested, and documented data models that transform raw data in our cloud data warehouse into analytics-ready datasets.
The ideal candidate is someone who wants to build, improve, and incorporate technologies that make the lives of our community more enriched, and who is motivated by delivering customer value. You’ll collaborate closely with our growing ED&A team and have a significant impact on the future of QuadReal.
This role can be based out of our Toronto or Vancouver office locations.

QUALIFICATIONS

• 5+ years of relevant analytics engineering or data engineering experience
• Advanced SQL skills and data modeling expertise
• Strong Experience with dbt and dimensional modeling concepts
• Experience with CI/CD practices for data pipelines
• Experience with cloud data warehousing technologies (MS Fabric, Snowflake)
• Experience with workflow orchestration tools like Airflow/Prefect
• Proficiency with enabling data optimized for BI tools (Power BI, Tableau, Looker)
• Strong communication skills, including presenting to leadership
• Collaborative approach with cross-functional teams
• Strategic thinking and problem-solving abilities
• Bachelor’s degree in technical field or equivalent experience

The following would be considered an asset:

• Experience with Azure SQL and Microsoft Fabric
• Familiarity with Airflow and Cosmos with dbt
• Passion for data governance and quality
• Experience in real estate or financial services
• Continuous learning mindset

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Note to Recruiters: QuadReal does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to QuadReal, directly or indirectly, will be considered QuadReal property. QuadReal will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for engaged services to submit resumes.
QuadReal Property Group will provide reasonable accommodation at any time throughout the hiring process for applicants with disabilities or for those needing job postings in an alternate format. If you require accommodation, please advise the Talent Acquisition team member you are working with and include the following: Job posting #, your name and your preferred method of contact

• Serve as a data subject matter expert, bridging the gap between business needs and technical implementation to deliver insights that drive decision-making.
• Define and document key business metrics while implementing data quality validation procedures to ensure consistent reporting across the organization.
• Collaborate with cross-functional teams to understand data needs and translate business requirements into technical solutions.
• Conduct data discovery by exploring data sources and understanding relationships between data elements to design data models that can be implemented as code.
• Design and develop data models and pipelines using dbt and SQL that transform raw data into analytics-ready datasets.
• Implement dimensional modeling techniques while establishing standards, testing procedures, and documentation practices.
• Provide best practices and feedback to contractual engineers to ensure standards are being followed across the team and related projects.
• Support self-service analytics by enabling stakeholders to create their own queries while increasing data literacy through training and documentation.