Analytics Engineer II
Build and own trusted marketing analytics data models and pipelines supporting attribution, paid marketing, SEO, and retailer marketing. The role requires 3+ years of analytics or data engineering experience, strong SQL and dimensional modeling skills, and hands-on experience with dbt, Snowflake, and Airflow.
About the job
Responsibilities
- Build and maintain dimensional data models and ETL pipelines supporting Paid Marketing, SEO, Retailer Marketing, and attribution analytics.
- Translate analytical needs and business questions into data requirements with Data Scientists, Analysts, and Marketing stakeholders.
- Own data quality through tests, documentation, monitoring, and root-cause resolution of data issues.
- Conduct code reviews, write design documents, and apply simple, reusable modeling patterns.
- Improve pipeline performance, reduce manual effort, enhance observability through logging, metrics, freshness checks, and quality checks, and participate in data-platform incident response.
Requirements
- 3–5 years of experience in Analytics Engineering, Data Engineering, or a closely related role, with ownership of production data models and pipelines.
- Strong SQL skills and experience building dimensional data models, including star schemas, fact and dimension tables, and slowly changing dimensions (SCDs).
- Hands-on experience with dbt, Snowflake, and Airflow.
- Working knowledge of marketing data and metrics, including paid media performance, attribution, and channel-level measurement, or the ability to ramp quickly.
- Ability to independently deliver complete data models and pipelines, manage multiple priorities, and write clean, documented, and tested code.
- Strong communication and collaboration skills across data, marketing, and engineering teams.
Nice-to-haves
- Experience partnering with Data Scientists on experimentation, attribution, or incrementality measurement.
- Familiarity with Google Ads, Meta, Google Analytics, and SEO tooling.
- Python experience for automation or advanced transformations.
- Experience using AI-assisted developer tools to generate tests, validate logic, or compare suggestions.
- Contributions to analytics engineering practices such as testing, documentation, or data quality standards.
Compensation
- Base pay: CA$145,000–$153,000 CAD annually.
- Eligible for a new-hire equity grant and annual refresh grants.
Skills
SQL, dbt, Snowflake, Airflow, Python, Dimensional Modeling, ETL, Data Pipelines, Data Quality, Google Ads, Meta Ads, Google Analytics, SEO
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