Lead Data Engineer (Analytics & Insights)

Join Agtonomy as a Lead Data Engineer (Analytics & Insights) and take ownership of transforming raw telemetry data into actionable insights for customers, partners, operations, engineering, and leadership. This hands-on role involves designing schemas, modeling metrics, and building React dashboards. You will also be accountable for the accuracy and trustworthiness of the metrics you produce.

• Concevoir les schémas, modéliser les métriques et expédier les tableaux de bord React.
• Définir les métriques qui comptent et transformer les questions floues en métriques fiables.
• Établir la qualité des données, la validation, la lignée et la documentation.
• Comfort working alongside a platform team that owns ingestion. You have experience collaborating with the teams developing the pipeline to ensure access to high quality, actionable data
• Strong Python and at least conversational comfort in one system language (Go, Rust, TypeScript, C++)
• 7+ years building production data systems, with meaningful time on both data modeling and analytics delivery
• Familiarity with semantic layers (dbt, Cube, MetricFlow, etc)
• A track record of turning raw telemetry into metrics non-technical stakeholders actually use and trust. You’ve turned loose high-level ideas into actionable and reliable analytics
• High standards for data quality. You've been the person on the hook when a customer-facing number was wrong, and you've built the systems that keep it from happening again
• Deep SQL fluency and strong opinions about modeling time-series and event data. ClickHouse experience is a strong plus; comparable OLAP systems (BigQuery, Snowflake, Druid, Pinot) translate
• Shipping experience in React. You've built analytics UIs or dashboards in a production web app and are comfortable owning the surface, not just the SQL behind it
• Experience in robotics, IoT, fleet management, automotive, or any domain where diverse physical devices produce telemetry at scale
• Experience building embedded analytics inside a product (customer-facing dashboards, not just internal BI tools)
• Experience shipping data experiences in React Native or other mobile frameworks
• Experience with ML-backed analytics — forecasting, anomaly detection, fleet health scoring, release regression detection