Mood is a dynamic e-commerce company focused on revolutionizing the legal cannabis industry in the U.S. They are seeking a Senior Analytics Engineer to design and maintain their analytics architecture, ensuring the reliability and scalability of their data models and pipelines. This role is integral to enabling AI-driven insights and enhancing the overall analytics infrastructure of the company.
Responsibilities:
- Design and maintain scalable data models that support reporting, experimentation, and machine learning
- Own the semantic layer and ensure consistent metric definitions across dashboards, analyses, and data products
- Develop and maintain transformation pipelines that turn raw data into clean, trusted analytics datasets
- Partner with analytics and business teams to translate analytical needs into well-structured data models
- Ensure the analytics layer is designed to support AI, experimentation frameworks, and predictive modeling
- Build and maintain reliable data pipelines using modern transformation frameworks
- Improve data freshness, performance, and scalability across the analytics stack
- Implement testing, monitoring, and validation frameworks to ensure data quality and reliability
- Work closely with data engineering to optimize warehouse performance and pipeline efficiency
- Support ingestion and modeling of new data sources across product, marketing, CX, and operations
- Power the dashboards and reporting used across marketing, product, operations, and leadership
- Optimize the BI layer to improve performance, usability, and trust in analytics outputs
- Reduce manual reporting by building reusable datasets and scalable reporting infrastructure
- Partner with analysts to ensure analytics workflows are efficient and well-supported by the data layer
- Design data models that support experimentation frameworks, predictive models, and AI applications
- Collaborate with data science to operationalize model outputs into reporting and decision workflows
- Ensure clean, well-documented datasets that enable faster development of machine learning and AI-driven products
- Help evolve Mood’s data platform toward a modern AI-enabled analytics architecture
- Maintain clear documentation for data models, metrics, and transformation logic
- Define and enforce standards for data quality, metric definitions, and modeling best practices
- Ensure stakeholders can easily understand and trust the data powering business decisions
- Contribute to a culture of data ownership, transparency, and high-quality analytics
Requirements:
- 4–7+ years of experience in analytics engineering, data engineering, or business intelligence
- Strong SQL skills and experience building scalable transformation pipelines
- Experience designing data models that power BI tools such as Looker, Looker Studio, Tableau, or similar
- Strong understanding of dimensional modeling, semantic layers, and analytics data architecture
- Experience building reliable data pipelines and implementing data testing/validation frameworks
- Comfort working closely with analysts, engineers, and business stakeholders
- Strong documentation habits and a commitment to building trusted analytics infrastructure
- Hands-on experience with modern analytics engineering tools (dbt or similar highly preferred)
- Experience working with cloud data warehouses (BigQuery strongly preferred)
- Experience supporting experimentation, growth analytics, or product analytics is a strong plus
- Familiarity with data structures required for machine learning or AI-driven analytics is a plus