About QuadReal Property Group

QuadReal Property Group is a global real estate investment, development and operating company headquartered in Vancouver, British Columbia. Its assets under management are $98.5 billion. From its foundation in Canada as a full-service real estate operating company, QuadReal has expanded its capabilities globally for investments in equity and debt in both the public and private markets. QuadReal invests directly through operating platforms in which it holds an ownership interest and via programmatic partnerships. 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.

Role Description

At QuadReal, the Data Quality & Controls Analyst sits at the intersection of Business, Data Governance, Analytics, and Data Engineering. The role is responsible for overseeing the daily end-to-end health of data across the Enterprise Data Platform (EDP), helping ensure that trusted data reaches business intelligence and reporting solutions.

The Enterprise Data & Analytics (EDA) team is looking for a Data Quality & Controls Analyst to operationalize data quality rules and technical controls across Airflow, dbt, Microsoft Fabric, SYNQ, and Power BI. You’ll translate approved business rules into executable checks, monitor data and pipeline health, coordinate issue resolution, and maintain the evidence needed to support current and evolving SOC 1 control requirements. The ideal candidate combines hands-on SQL and data engineering knowledge with robust operational discipline and transparent stakeholder communication. You’ll work closely with Business Data Stewards, Data Governance, analytics engineers,



data engineers, BI developers, and control partners to improve data trust and strengthen the reliability of enterprise reporting. This role can be based out of our Toronto or Vancouver office locations.

Responsibilities

- Daily Data Operations: Oversee the daily end-to-end data process by monitoring Airflow workflows, dbt builds, tests and source freshness, Microsoft Fabric pipelines and notebooks, SYNQ alerts, and downstream Power BI impacts.
- Issue Management: Log, prioritize, route, and track data quality and pipeline issues to resolution within agreed service levels; coordinate reruns, backfills, and recovery validation without bypassing required controls.
- Data Quality Rules: Partner with Business Data Stewards and Data Governance to translate approved business rules into executable freshness, completeness, uniqueness, validity, referential integrity, schema, and anomaly checks.
- Data Quality Tooling: Configure and maintain monitors, ownership, alert routing, lineage, incidents, and data quality metrics in SYNQ, supported by dbt tests and SQL-based validation where appropriate.
- Threshold Management: Use data profiling, historical patterns, statistical analysis, business materiality, and feedback from stakeholders to establish and tune thresholds while reducing false-positive alerts.
- Control Evidence: Maintain complete, attributable,



and time-stamped evidence that controls operated as designed, including run histories, dbt results and artifacts, SYNQ incidents, tickets, approvals, reconciliations, and remediation records.
- SOC 1 Support: Support control walkthroughs, evidence requests, sample testing, exception documentation, and remediation activities in partnership with Risk, Controls, and Audit stakeholders.
- Quadrant Overrides: Operate and support the Quadrant override functionality for approved business corrections, ensuring each change is authorized, traceable, technically validated, and reflected correctly in downstream data. Business owners approve changes; the analyst supports the tooling and does not self-approve overrides.
- Manual File Controls: Support controlled manual file ingestion by validating file identity, format, schema, timing, approvals, ingestion results, and reconciliations so manual inputs remain reproducible and auditable.
- Lineage and Reporting Impact: Use metadata and lineage to understand how upstream failures or changes affect critical datasets, metrics, semantic models, and Power BI reports, and communicate business impact to the appropriate owners.
- Standards and Documentation: Maintain runbooks, control documentation, data quality definitions, known-issue guidance, and operating procedures; identify opportunities to automate evidence and reduce recurring incidents.
- Separation of Duties: Implement technical controls and approved governance standards while maintaining clear role boundaries. Data Governance owns the operating model and policy, business owners approve business corrections, and EDA owns technical implementation and execution.

Experience and Qualifi

📌 Data Quality and Controls Analyst (Toronto)
🏢 QuadReal Property Group
📍 Toronto