Software Engineer - Data Analytics & Tools

Start date: As soon as possible

Since its founding in 2015, 1X has been at the forefront of developing advanced humanoid robots designed for household use. Our mission is to create an abundant supply of labor via safe, intelligent humanoids.

We strive for excellence in all we do, solving some of the hardest problems in robotics with the world’s most talented individuals. Every part of our robots is designed and produced in-house—from motor coils to AI—reflecting our vertically integrated approach. At 1X, you’ll own real projects, be recognized for your achievements, and rewarded based on merit.

We believe the best work is done when collaborating and therefore require in-person presence in our office locations.

We are seeking a highly skilled Software Developer with deep expertise in database development, data analysis, and data analytics tool creation. In this role, you will be responsible for integrating and normalizing data from diverse sources, building performant data pipelines, and creating powerful visualization tools (Power BI, Tableau, custom dashboards) that enable precise decision-making, progress tracking, and issues management across the organization. 

Why this job is exciting

• Shape data infrastructure and analytics tools critical to the future of humanoid robotics

• Build decision intelligence systems that drive real-world outcomes for 50+ DoF biped robots

• In time, your work will support thousands of robots operating safely in dynamic environments

Responsibilities

• Design, develop, and optimize manufacturing and supply chain databases, data warehouses, and ETL pipelines to integrate data from diverse sources

• Architect data models and normalization strategies to ensure consistency, accuracy, and usability

• Build and maintain analytics and visualization tools using Power BI, Tableau, and custom dashboards

• Collaborate with manufacturing, supply chain, and engineering teams to define KPIs and reporting solutions

• Develop systems for tracking progress against schedules, forecasting capacity, and managing risks

• Optimize queries and database performance for large-scale datasets

• Implement data governance, security, and quality control mechanisms