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Quantitative Data Engineer Jobs in Toronto, ON (NOW HIRING)

Bachelor's degree in a quantitative field (Statistics, Economics, Data Science, Engineering) or related field of study. * 12-15+ years in data architecture, data engineering, or related roles

As a Data Scientist in the Pay, Integrity & Identity org, you will collaborate with our world class ... quantitative field such as statistics, economics, applied math, operations research or engineering ...

... quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Economics) or ... High judgment on data quality, privacy/security, and risk * Strong storytelling and executive ...

About the team Our Data Science team partners deeply with teams across Stripe to ensure that our ... A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics ...

Bachelor's degree in Statistics, Maths, Engineering, Economics, or another quantitative field * 4-5+ years in similar analytical roles * Proficient in SQL and experience with complex data queries

Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI ... A degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative ...

Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI ... A degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative ...

You will partner closely with Data Engineers, Product Managers, and Revenue leaders to embed ... Degree in a STEM discipline (Data Science, Statistics, Computer Science, or a related quantitative ...

Showing results 41-60

Quantitative Data Engineer information

What is a quantitative data engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

How does a quantitative data engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.

What are the key skills and qualifications needed to thrive as a quantitative data engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

What are popular job titles related to Quantitative Data Engineer jobs in Toronto, ON?

For Quantitative Data Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Toronto, ON look for?

The top searched job categories for Quantitative Data Engineer jobs in Toronto, ON are:

Infographic showing various Quantitative Data Engineer job openings in Toronto, ON as of June 2026, with employment types broken down into 2% As Needed, 91% Full Time, 5% Part Time, and 2% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Senior Data Scientist, Measurement & Analytics

Publicis Groupe Holdings B.V

Toronto, ON โ€ข On-site

Full-time

Re-posted 10 days ago


Job description

Company Description

Saatchi & Saatchi is an advertising agency with the belief that creativity, data, media and technology should all work together, and we use that to influence human behavior and drive success for clients. S&S is one of the world's largest agency networks with 114 offices and more than 6000 employees globally. Here in our Toronto office we work with some of the countries most valued brands including Toyota, Lexus, Quesada and Mondelez just to name a few. We're an award winning agency in both creativity and effectiveness, so it's really important for us here to convert that innovation and the great ideas into real tangible business results for the organization.

OverviewAbout the Role

We are seeking a Senior Data Scientist, Measurement & Analytics to lead the development of advanced measurement frameworks, reporting solutions, data infrastructure, and analytical models that support marketing and business decision-making.

This role combines data science, analytics engineering, digital measurement, cloud data architecture, and stakeholder consulting to deliver scalable analytics solutions across web, media, and customer experience initiatives. The successful candidate will transform complex datasets into actionable insights, build reporting automation, develop statistical models, and help drive measurement excellence across the organization.

ResponsibilitiesKey ResponsibilitiesMeasurement Strategy & Analytics Leadership
  • Lead the development and evolution of digital measurement frameworks and KPI strategies.
  • Establish measurement methodologies that support business objectives and performance tracking.
  • Translate business questions into analytical approaches and actionable recommendations.
  • Serve as a subject matter expert on digital measurement, attribution, and customer behavior analytics.
Data Science & Advanced Analytics
  • Develop and maintain regression models, forecasting models, attribution methodologies, and marketing performance analyses.
  • Conduct exploratory analyses to identify key business drivers, trends, and optimization opportunities.
  • Design measurement approaches for testing and experimentation initiatives.
  • Apply advanced analytical techniques to solve complex business problems and support strategic decision-making.
Analytics Engineering & Data Infrastructure
  • Design, build, and maintain scalable analytics and reporting solutions.
  • Develop automated data pipelines that integrate web, media, and business data sources.
  • Build data transformation, validation, and quality assurance processes.
  • Support the modernization and automation of analytics infrastructure and reporting workflows.
Dashboarding & Reporting
  • Lead the design and development of executive dashboards and reporting solutions.
  • Create automated scorecards and performance reporting frameworks.
  • Develop scalable data models that reduce manual reporting effort and improve consistency.
  • Partner with stakeholders to deliver meaningful and actionable reporting experiences.
Digital Analytics & Measurement Implementation
  • Own measurement architecture and tracking strategy across digital properties.
  • Lead implementation, validation, and troubleshooting of analytics and advertising technologies.
  • Ensure data collection integrity, measurement accuracy, and reporting quality.
  • Partner with internal and external teams to support analytics requirements for new initiatives and platform enhancements.
Stakeholder & Client Leadership
  • Act as a trusted advisor on analytics, reporting, and measurement strategy.
  • Present analytical findings and recommendations to senior stakeholders.
  • Collaborate with media, search, web, and technology teams to deliver integrated analytics solutions.
  • Manage multiple high-priority projects while maintaining quality and delivery standards.
QualificationsTechnical RequirementsAdvanced Expertise Required
  • Google Analytics 4 (GA4)
  • Google Tag Manager (GTM)
  • SQL
  • Python
  • BigQuery
  • Power BI or equivalent business intelligence platforms
  • Statistical analysis and modeling
  • Regression analysis
  • Forecasting and trend analysis
  • Attribution methodologies
  • Dashboard development and reporting automation
  • Data visualization and storytelling
  • Marketing and digital measurement frameworks
  • Conversion tracking and analytics implementation
Strong Working Knowledge
  • Google Cloud Platform (GCP)
  • API integrations
  • Data pipeline development
  • Cloud-based analytics architectures
  • Marketing performance analysis
  • Media measurement and attribution
  • Experimentation and testing methodologies
  • Data governance and quality assurance
Skills & CompetenciesTechnical Skills
  • Advanced analytical and quantitative problem-solving capabilities.
  • Strong data engineering and data transformation expertise.
  • Ability to work with large-scale structured and unstructured datasets.
  • Expertise in reporting automation and analytics solution development.
  • Strong data visualization and storytelling skills.
Business & Leadership Skills
  • Excellent communication and presentation skills.
  • Ability to translate complex technical concepts into business recommendations.
  • Strong stakeholder management and consulting capabilities.
  • Ability to manage multiple concurrent priorities in a fast-paced environment.
  • Strong attention to detail and commitment to data quality.
Personal Attributes
  • Self-starter with strong ownership and accountability.
  • Strategic thinker who connects analytics to business outcomes.
  • Collaborative team player who works effectively across technical and non-technical teams.
  • Continuous learner who stays current on analytics, measurement, and technology trends
Additional Information

Salary

Transparency matters to us. The salary for this position is $CAD 80,000 - 100,000 per year. Actual compensation within this range will be based on a variety of factors, including relevant experience, knowledge, skills, and applicable certifications. This range reflects what we reasonably expect to offer based on current market data.

AI Use

We use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications or analyzing resumes. These tools assist our recruitment team but never replace human decision-making. We believe in a human-first approach, where your experience and potential are recognized by people.

Saatchi is an equal opportunity employer and we welcome and encourage applications from all interested parties. Accommodations are available, upon request, for all stages of the interview and employment process for those with a disability or medical need during any stage of the recruitment process. We thank all candidates for their interest inย Publicisย Media, however, only those candidates selected for an interviewย will be contacted.ย 

Employment Type: FULL_TIME