Trigo’s in-store AI systems are generating a wealth of real-world data—from product movement to neural network outputs to store-level events. We're looking for a hands-on, business-minded Analytics Engineer to build the infrastructure and tooling that turns this data into operational gold.

You’ll be the first data hire in our new Operations Insights team, responsible for designing the operations data platform, generating insights for internal and external stakeholders, and helping our business teams deliver measurable impact. This is a hybrid role that combines data engineering with analytics and product thinking—you’ll build, analyze, and consult.

From designing the data warehouse to crafting performance dashboards and investigating edge-case customer issues, you’ll be the go-to person who makes Trigo’s data accessible, trustworthy, and powerful.

• Design and implement the operational data platform, consolidating data from R&D systems
• Build and maintain data pipelines and tables for store performance, deployment health, and system diagnostics
• Collaborate with the Director of Customer Value & Insights and Expansion Managers to define KPIs and surface business insights
• Conduct exploratory data analysis to support tough customer and deployment challenges
• Build internal tools and dashboards that empower teams to self-serve critical data
• Investigate anomalies, edge cases, and complex failure scenarios to improve deployments
• Maintain data quality, documentation, and observability as we scale to hundreds of stores

• 4+ years of experience as an Analytics Engineer, Data Engineer, or Full-Stack Data Developer
• Expertise in SQL and Python; experience with modern data stacks (dbt, Airflow, etc.)
• Experience designing data models and pipelines for analytics and reporting
• A pragmatic mindset—you solve problems, not just build pipelines
• Comfort working directly with non-technical stakeholders to understand their needs
• Curiosity about the physical world—excited to work with retail, hardware, and real-time system data

• Exposure to computer vision or edge deployments
• Experience with BI tools (Looker, Tableau, or similar)
• Familiarity with ML pipelines, anomaly detection, or time-series data
• Interest in building data products that will eventually serve Trigo customers