Analytics Engineer, Sentry at Anduril Industries in Irvine, CA

Summary: Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. The Analytics Engineer for Sentry will be responsible for designing and maintaining data systems that provide strategic insights and enhance operational efficiency through data analysis. Responsibilities: - Build and maintain data pipelines and analytical systems: Design data workflows that ingest, transform, and model data from diverse sources (deployment systems, inventory databases, monitoring tools, business systems), ensuring data quality and accessibility - Develop dashboards and analytics that shape decision-making: Create data products ranging from ad hoc analyses for rapid iteration to scalable dashboards and trackers that provide visibility into deployment tracking, inventory status, component lifecycle, fleet performance, and system reliability - Own the full product lifecycle: Act as PM, designer, and builder for analytics tools—defining requirements, designing user experiences, building technical solutions, and iterating based on user feedback - Collaborate to bridge technical and operational needs: Partner closely with cross-functional teams to understand their data challenges and translate them into effective data solutions, working within systems like ERP, MRP, and other operational platforms - Drive operational efficiency through data analysis: Perform quantitative analyses including deployment data validation, inventory reconciliation, trend analysis, variance investigation, and root-cause analysis to identify bottlenecks and optimize processes - Enhance Sentry fleet management and sustainment: Utilize data to understand fleet performance in the field, optimize deployment strategies, and improve the efficiency of sustainment operations for the growing Sentry fleet - Iterate based on feedback and evolving requirements: Continuously improve data products by incorporating stakeholder feedback and adapting to changing operational needs as Sentry scales - Document and champion data quality: Ensure data definitions, business logic, and methodologies are well-documented and understood across teams, promoting data literacy and self-service capabilities Required Qualifications: - 1–3 years of professional experience in an analytics-focused role (Analytics Engineer, Data Engineer, Data Analyst, or similar) - Degree in a quantitative or analytical field (Statistics, Engineering, Data Science, Math, Operations Research, Computer Science) or equivalent practical experience - You're technical—you are data-driven, understand systems, and can write SQL and Python (or similar analytical languages) to manipulate and analyze data - You're a builder—you take ownership end-to-end, from defining the problem to designing the solution to building and deploying it - You're clear—you communicate effectively in both technical and non-technical contexts, translating business problems into data solutions - You have a strong bias for action and a preference for designing better solutions rather than patching around existing problems - You thrive on untangling complex, messy problems and are energized by creating order from chaos in a rapidly evolving operational environment - Ability to work cross-functionally with engineering, product, supply chain, and operations teams to drive outcomes - Must be authorized to work in the United States Preferred Qualifications: - Experience building business-facing dashboards and visualizations using tools such as Palantir Foundry, Tableau, Looker, Power BI, Streamlit, or similar - You can build full-stack solutions, including frontend development with React or similar frameworks when needed - Familiarity with data pipeline concepts, ETL processes, or data engineering principles - Experience working within business systems (ERP, MRP, MES, inventory management platforms) or supply chain analytics - Background in hardware product lifecycle operations, manufacturing environments, or complex hardware/software systems - Experience with monitoring and alerting tools (DataDog, Grafana, or similar) - Knowledge of reliability engineering metrics (MTBF, failure analysis, deployment tracking) or fleet management concepts - Background working in fast-paced environments without a playbook, particularly in hyper-growth or startup settings - Experience in defense, aerospace, robotics, autonomy, or mission-critical technology environments Required Skills: SQL, Python, Data engineering principles, Data pipeline development, Dashboard, data visualization, ETL processes, Business systems ERP, Business systems MRP, Business systems MES, Supply chain analytics, Reliability engineering metrics, Fleet management concepts, Bias for action Benefits: Comprehensive, competitive benefits package, Top-tier benefits for full-time employees