Data Quality Specialist

Q4; Old Toronto; On-site; CAD 60,000 - 80,000; Full time

Job summary

An innovative company is seeking a Data Quality Lead to spearhead efforts in ensuring data integrity and quality across systems. This role involves collaborating with data engineers and stakeholders, conducting rigorous data validations, and implementing data governance policies. As a key player in the development team, you'll drive initiatives to enhance data collection and transformation processes, utilizing your expertise in SQL and data quality tools. If you're passionate about data and excited to make a significant impact in a fast-paced environment, this opportunity is perfect for you.

Qualifications

• 5+ years in data analysis with a focus on large datasets.
• Expertise in SQL and data quality tools is essential.

Responsibilities

• Lead data quality control and enhance quality assurance processes.
• Collaborate with teams to ensure data integrity and compliance.

Skills

Data Analysis

SQL

Data Quality Tools

Data Governance

Data Visualization (Tableau, Power BI)

Python/R Scripting

Agile Development

Problem-Solving

Tools

Tableau

Power BI

Snowflake

BigQuery

Job description

At Q4, we make an impact together, obsess over our customer, operate with integrity, and bring big ideas to life.

Q4 is charting a bold new path for investor relations as the first AI-driven IR Ops Platform, providing everything an IR team needs to succeed on a single, powerful platform. The Q4 Platform enables public companies to attract, manage, and understand investors - all in one place. Over 2,600 customers, including many of the most respected brands in the world, trust Q4 to help drive premium valuations for their companies. Only Q4 offers a tech stack holistically designed to equip IR teams with data, insights, and smart workflows that power remarkable outcomes. Learn more at q4inc.com .

We hire smart, curious, and talented people to push boundaries, reimagine what’s possible, and turn challenges into opportunities. All while keeping the needs of our clients at the heart of everything we do.

Come grow with us!

The Role

Leading the data quality control effort and enhancing quality assurance throughout the software development life cycle. Provide data governance, data quality leadership and guidance to the team. This role is an advocate and driver of Product build quality and measurements in the Development team.

What you'll do

• Collaborate with data engineers, and business stakeholders to understand data sources, flows, metadata, and usage across systems.
• Contribute to agile story refinement/defining requirements.
• Conduct source-to-target data validation, ensuring compliance with design specifications and identifying inconsistencies or gaps.
• Build and execute complex SQL-based tests to assess data completeness, integrity, and accuracy in data pipelines.
• Perform root cause analysis on data quality issues and recommend scalable solutions, including data validation controls.
• Develop and maintain data profiling reports, using tools to analyze patterns and uncover anomalies.
• Actively communicate data quality risks to stakeholders, highlighting the impact on reporting, decision-making, and downstream processes.
• Lead initiatives to improve data collection, storage, and transformation processes by working closely with data engineering teams.
• Build and maintain data quality dashboards and reports to monitor trends and track resolution of identified issues.
• Design and enforce data governance policies, including standards for data accuracy, consistency, and usage.
• Document and maintain data validation rules, workflows, and audit processes to ensure continuous quality improvement.
• Support data migration or integration projects, validating the integrity of datasets during transitions.

Skills & Qualifications

• 5+ years of experience in data analysis, profiling, or data quality auditing, with a strong focus on large and complex datasets.
• Expertise in SQL for querying, auditing, and validating data across multiple systems (Databases, Warehouses, and ETL pipelines).
• Strong knowledge of data quality tools and frameworks.
• Familiarity with data governance best practices, metadata management, and data cataloging tools.
• Experience with data visualization tools (e.g., Tableau, Power BI) to create data quality dashboards.
• Solid understanding of data models, data pipelines, and their performance in a modern data ecosystem (e.g., Snowflake, BigQuery).
• Hands-on experience with automating data quality checks using Python, R, or similar scripting languages.
• Strong problem-solving and analytical skills, with a proven ability to identify, document, and resolve data quality gaps.
• Knowledge of Agile development processes and experience working in cross-functional data teams.
• Ability to communicate complex data issues to technical and non-technical stakeholders in clear, actionable terms.
• Strong focus on data reliability, scalability, and operational excellence.