Role Description The Principal Engineer, Data Solutions is a senior technical leadership position responsible for ensuring the quality, scalability, and effectiveness of data and analytics solutions within QuadReal's Enterprise Data & Analytics function. Reporting to the Director of Data Solutions, this role serves as the technical right‑hand, setting standards, mentoring team members, evaluating complex solutions, and delivering hands‑on technical work for the organization’s most challenging data problems. Responsibilities Technical Leadership & Standards (40%)Set the Technical Bar: Define and enforce standards for data modeling, analytics engineering, and BI development across all Data Solutions squads. Solution Evaluation: Review and validate technical designs for major initiatives, ensuring architectural soundness and alignment with enterprise patterns. Vendor Management: Evaluate proposals from consulting partners and technology vendors; hold vendors accountable for quality and delivery. Quality Assurance: Conduct code reviews, model reviews, and technical assessments to maintain high standards in alignment with governance best practices. Hands‑On Technical Delivery (35%)Build Reference Implementations: Create exemplary data models, dbt projects, and BI dashboards that serve as templates for the organization. Solve Complex Problems: Tackle technical challenges beyond current team capabilities, from advanced SQL optimization to complex dimensional modeling. Develop Data Models: Design and implement scalable, well‑documented data models using dbt, Snowflake/Fabric, and modern analytics engineering practices. Hands‑On Coding: Write production SQL, Python, and data transformation logic daily (60%+ hands‑on work). Enablement & Mentorship (25%)Upskill Data Analysts/Product Managers: Teach effective due diligence, solution design, and technical requirement translation.



Mentor Analytics Engineers: Provide structured guidance on data modeling patterns, dbt best practices, and analytical thinking. Conduct Training: Lead technical workshops, lunch‑and‑learns, and documentation initiatives. Foster Technical Culture: Build a culture of engineering excellence, continuous learning, and quality‑first thinking. Experience and Qualifications 6-8+ years in analytics engineering, data engineering, business intelligence, or related technical roles. Proven track record designing and implementing enterprise‑scale data solutions ($1B+ organization preferred). Deep expertise in data modeling methodologies (dimensional modeling, data vault, metrics layers, etc.). Production experience with modern data stack tools: dbt, Snowflake/Databricks/Fabric, SQL, Python. Hands‑on BI development using Power BI, Tableau, or similar enterprise platforms. Vendor/partner management experience evaluating and holding consulting firms or technology vendors accountable. Mentorship experience uplifting junior and mid‑level data professionals. Expert‑level SQL (complex queries, optimization, window functions, CTEs). Data modeling and dimensional design (star schema, snowflake, data vault). dbt or equivalent transformation frameworks. Modern cloud data warehouses (Fabric, Databricks). Power BI or Tableau (DAX, calculated fields, performance optimization). Python for data analysis and automation. Apache Airflow or similar orchestration tools. Git/version control and CI/CD practices. Data quality, testing,



and observability frameworks. Data governance and security best practices. Key Competencies Technical Judgment: Evaluate solutions and articulate trade‑offs clearly; know when to be pragmatic vs. principled. Teaching Ability: Explain complex technical concepts to non‑technical audiences and mentor others effectively. Hands‑On Mindset: Prefer writing code to drawing diagrams; lead by example. Intellectual Curiosity: Stay current with contemporary data practices; eager to learn and experiment. Stakeholder Management: Translate business requirements into technical solutions and push back when needed. Ownership Mentality: Take pride in quality; avoid shipping “good enough” when excellence is achievable. Preferred Experience Real estate, financial services, or asset management domain experience. Experience with Azure ecosystem (Fabric, Data Factory). Compensation and Benefits The expected annualized base salary range for this role is $120,000‑$150,000. QuadReal offers a competitive total rewards package that may include a performance‑based incentive plan, comprehensive health & dental benefits, a pension plan, and paid time off. Additional Information We value diverse experiences and perspectives. Even if your skills don’t align 100% with the listed qualifications or salary range, we encourage you to apply – you may be a great fit for this role or others in our community. 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. For those requiring 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. #J-18808-Ljbffr

📌 Principal Engineer, Enterprise Data & Analytics - $120,000 - $150,000 A Year (Toronto)
🏢 QuadReal
📍 Toronto