Analytics Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Analytics Engineer based in Canada.

As an Analytics Engineer II, you will help build and evolve the data foundations that power marketing analytics, attribution, and investment decisions at significant scale. You’ll independently design and deliver reliable dimensional models and ETL pipelines that Data Scientists, Analysts, and Marketing teams can trust. The role combines hands-on data engineering with close collaboration across technical and business teams to turn complex questions into decision-ready datasets. You’ll take end-to-end ownership of your work, from requirements and development through testing, documentation, monitoring, and continuous improvement. You’ll also help strengthen engineering practices through thoughtful code reviews, design discussions, and reusable modeling patterns. This is an opportunity to make a measurable impact in a flexible, remote-first environment while growing toward broader technical ownership of marketing data.

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Accountabilities:

• Independently design, build, and maintain high-quality dimensional data models and ETL pipelines supporting paid marketing, SEO, retailer marketing, attribution, and broader marketing analytics.

• Partner closely with Data Scientists, Analysts, and Marketing stakeholders to translate analytical questions and business needs into clear data requirements and trusted, decision-ready datasets.

• Take ownership of data quality for the models and pipelines you develop by implementing tests, documentation, monitoring, and root-cause resolution for data issues.

• Conduct thorough code reviews and communicate technical designs before implementation, applying simple and reusable modeling patterns that improve the overall quality of the data environment.

• Improve existing marketing data pipelines by reducing manual effort, enhancing performance, and strengthening observability through logging, metrics, freshness checks, and quality monitoring.

• Contribute to incident response for the data platform and work proactively to identify opportunities to improve reliability, maintainability, and operational efficiency.

• Manage multiple priorities with minimal oversight while delivering complete data assets from initial requirements through production implementation and ongoing support.

Requirements:

• Bring 3–5 years of experience in Analytics Engineering, Data Engineering, or a closely related field, with hands-on ownership of production data models and pipelines.

• Demonstrate strong SQL expertise and practical experience designing well-architected dimensional data models, including star schemas, fact and dimension tables, and slowly changing dimensions.

• Have hands-on experience with modern data stack technologies such as dbt, Snowflake, and Airflow.

• Possess working knowledge of marketing data and metrics, including paid media performance, attribution concepts, and channel-level measurement, or demonstrate the ability to learn these areas quickly.

• Show the ability to independently deliver complete data models and pipelines while writing clean, well-documented, and well-tested code.

• Be an effective communicator who can collaborate across data, marketing, and engineering teams to understand requirements and deliver practical solutions.

• Experience partnering with Data Scientists on experimentation, attribution, or incrementality measurement is a plus.

• Familiarity with marketing platforms such as Google Ads, Meta, Google Analytics, or SEO tools is desirable.

• Python experience for automation or advanced transformations is beneficial, as is experience establishing analytics engineering standards around testing, documentation, and data quality.

• Comfort using AI-assisted developer tools to improve development speed and code quality, including generating tests, validating logic, and evaluating technical suggestions, is valued.

Benefits:

• Base salary of $139,000–$146,500 CAD for successful candidates in Canada.

• Eligibility for a new-hire equity grant and annual equity refresh grants.

• Fully remote work within Ontario, Alberta, British Columbia, or Nova Scotia.

• Flexibility to choose where you do your best work, supported by a Flex First approach.

• Highly competitive compensation and benefits designed for employees across different locations.

• Opportunity to work on high-impact marketing data foundations that inform significant investment and growth decisions.

• Exposure to modern data technologies, analytics engineering practices, marketing attribution, experimentation, and data quality at scale.

• Collaborative environment with close partnerships across Data, Marketing, Engineering, and Science teams.

• Opportunities to grow toward broader technical ownership and leadership within the data organization.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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