Own enterprise data quality standards and monitoring across source systems, ETL pipelines, and cloud warehouses. Profile and validate data, perform root-cause analysis, design ETL test strategies, and prevent bad data from reaching models and dashboards. Partner with Data Engineering, Data Science, and Governance to define validation criteria, report KPIs, and mentor junior analysts.
Senior Data Quality Analyst
Vaughan, ON
About the Role
We are hiring a Senior Data Quality Analyst to own data quality across our enterprise data platforms and the analytics, forecasting, and AI/ML systems built on top of them. You will be the primary safeguard between raw operational data flowing through source systems and ETL pipelines and the models and dashboards that depend on it — defining what "trustworthy data" means for the business and building the frameworks that keep it that way.
You will work closely with Data Engineering, Data Science, and Business Intelligence to catch data issues before they reach production models or executive dashboards, and to build lasting automated safeguards rather than one-off fixes.
What You'll Do
Data Quality Strategy & Monitoring
- Define and own enterprise data quality standards, rules, and scorecards covering accuracy, completeness, consistency, timeliness, and uniqueness across core operational and analytical datasets.
- Build automated data quality monitoring and alerting so issues are caught before they reach downstream models or dashboards, not after.
- Establish and report on data quality KPIs and trends to Engineering, Data Science, and Business leadership.
Profiling, Validation & Root Cause Analysis
- Profile and assess data across source systems, ETL pipelines, data warehouses, and reporting layers to identify anomalies and diagnose root causes, not just symptoms.
- Validate the data used by downstream forecasting, optimization, and reporting models for correctness before it reaches production.
- Design and execute test strategies for ETL processes and pipeline changes; support UAT and reconciliation efforts.
Governance & Cross-Functional Partnership
- Partner with Data Governance on standards, stewardship, metadata management, and compliance requirements.
- Translate business data requirements into concrete, measurable validation criteria alongside Data Engineering and Data Science.
- Communicate findings, risk, and remediation plans clearly to both technical and business stakeholders; mentor junior analysts.
What You'll Need
Required Qualifications
- 7+ years of experience in Data Quality, Data Analysis, Data Governance, or Business Intelligence.
- Advanced SQL and hands-on experience profiling and validating large, complex datasets across ETL pipelines and cloud data warehouses.
- Solid grounding in data governance, lineage, metadata management, and master data concepts.
- Experience working with both relational and non-relational data stores.
- Strong analytical rigor, attention to detail, and stakeholder communication skills.
Preferred Qualifications
- Experience supporting AI/ML or advanced analytics initiatives, including validating data that feeds forecasting or optimization models.
- Experience with data quality automation or monitoring frameworks.
- Experience working within Agile delivery environments.
- Background in logistics, supply chain, retail, financial services, or healthcare data.
- Knowledge of relevant regulatory or data compliance frameworks.
Tools & Technologies
SQL •ETL / Data Pipelines • Cloud Data Warehousing • Data Governance • Data Quality Automation • Agile
TechBlocks Vaughan, Ontario, CAN Office
Suite 4,, 399 Applewood Crescent, , , Vaughan, Ontario , Canada, L4K 4J3
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