Analytics Engineer, Lifecycle Efficiency

📋 Description

• Design, build, and maintain production data models for incentives, promotions, lifecycle analytics.
• Collaborate with Data Engineering to model data from multiple systems and implement ELT patterns.
• Define KPI definitions and enable self-serve analytics with clean semantic models and LookML.
• Set data quality standards with automated testing, lineage, and monitoring for trusted dashboards.
• Collaborate with Product, Marketing, and Engineering to scope requirements and deliver high-impact datasets.
• Continuous improvement of pipeline performance, reliability, and cost efficiency; promote best practices.

🎯 Requirements

• 4+ years in analytics engineering, data engineering, or BI building production data models in a cloud stack.
• Advanced SQL proficiency (joins, window functions, optimization) with Snowflake, BigQuery, or Redshift.
• 2+ years implementing and maintaining dbt projects in production with Git workflows.
• Hands-on experience orchestrating ELT/ETL pipelines with Airflow, Dagster, or similar.
• Experience building semantic layers and BI models (Looker/LookML or equivalent) for self-serve analytics.
• Automated data quality testing and data observability, with ownership of documentation and lineage.

🎁 Benefits

• Remote-first policy with flexible work locations.
• Equity grants and annual refresh grants.
• Flex First remote policy and Canada provincial eligibility.
• Competitive benefits and strong team collaboration.