Analytics Engineer II

This is a fully remote position, open to applicants in Canada.

📋 Description

• Develop and uphold dimensional data models and ETL pipelines that support Paid Marketing, SEO, Retailer Marketing, and attribution.

• Provide comprehensive data assets from start to finish with minimal supervision.

• Work collaboratively with Data Scientists, Analysts, and Marketing stakeholders to convert analytical needs into data specifications.

• Supply reliable, decision-ready datasets.

• Take ownership of data quality through testing, documentation, monitoring, and resolving root causes of data issues.

• Conduct code reviews and share design concepts prior to implementation.

• Implement straightforward, reusable modeling patterns.

• Enhance marketing data pipelines to minimize manual tasks and boost performance.

• Increase observability through logging, metrics, freshness checks, and quality assessments.

• Engage in data platform incident response.

⛳️ Requirements

• 3–5 years of experience in Analytics Engineering, Data Engineering, or similar roles.

• Hands-on experience with production data models and pipelines.

• Proficient SQL skills.

• Experience in constructing dimensional data models, including star schemas, fact/dimension tables, and Slowly Changing Dimensions (SCDs).

• Familiarity with dbt, Snowflake, and Airflow.

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

• Capacity to deliver complete data models and pipelines autonomously.

• Ability to manage multiple tasks effectively.

• Skill in writing clean, well-documented, and well-tested code.

• Strong communication and collaboration abilities across functions.

• Experience collaborating with Data Scientists on experimentation, attribution, or incrementality measurement is preferred.

• Familiarity with Google Ads, Meta, Google Analytics, and SEO tools is preferred.

• Experience with Python is preferred.

• Comfort in using AI-assisted developer tools is preferred.

• Experience in contributing to analytics engineering best practices is preferred.

🏝️ Benefits

• New hire equity grant.

• Annual refresh grants.

• Flexible choice of work location (home, office, or coffee shop).

• Regular in-person events.

• Market-competitive compensation and benefits.