Senior Analytics Engineer

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