Data Engineer, AQNav at Sandboxaq

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY SandboxAQ's AQNav (Quantum Navigation) team builds global, GPS-independent, navigation solutions from military and commercial aircraft to autonomous submersible platforms. We are the bridge between cutting-edge quantum sensing research and real-world operations, working directly alongside the defense customers and platform integrators at the highest levels to prove that magnetic navigation works where it matters most. The AQNav team is looking for a highly-accomplished Data Engineer to help take us to the next level. This role is that role you always wanted, to be able to work on cutting-edge technology. You get to join and help build out infrastructure that will empower every member of the team with the data they need, pipelines to help them move faster, and processes that will accelerate and validate our models. The tools and pipelines you help build will directly impact the team's success. We are looking for a data engineer that thrives wearing a variety of hats and enjoys working alongside a diverse group including physicists, ML researchers, hardware engineers, software engineers, data engineers, field ops personnel, navigation engineers, customer facing leaders, and managers at different levels. KEY RESPONSIBILITIES: - Data Pipeline Development & Maintenance: Work across a mixed-maturity pipeline environment - Data Modeling: Build and optimize data models that serve a diverse set of consumers. You'll make the data accessible and trustworthy, not just available - Simulation Data Integration: Work within the in-house simulation suite to add data-capturing capabilities and ensure simulation outputs feed cleanly into downstream pipelines alongside real-world field data - Data Quality & Observability: Instrument pipelines with quality checks, anomaly detection, and alerting so issues surface early - Cross-Functional Data Support: Translate ambiguous asks into well-defined requirements, repeatable datasets and lightweight Dashboards that the team can use independently going forward - Data Platform Infrastructure Contribution: Improve the features and reliability of our internal data platform over time - Documentation: Own the technical documentation for pipelines, data models, and schemas you touch. In a team this cross-functional, good documentation is a force multiplier ESSENTIAL SKILLS & EXPERIENCE: - 3+ years of industry experience as a Data Engineer in a startup or fast-moving environment. - Strong proficiency in Python and SQL, with hands-on experience building production-grade data solutions. - Experience designing and maintaining data pipelines and data models/warehouses that process large, structured scientific or engineering datasets. - Hands-on experience building on AWS (e.g., S3, ECS, Lambda, IAM) combined with CI/CD and containerization (e.g., GitHub Actions or CircleCI, Docker) to automate, deploy, and maintain data and ML workloads in the cloud. - Practical MLOps experience: setting up and operating MLOps frameworks (e.g., MLFlow, DVC) HIGHLY DESIRED SKILLS & EXPERIENCE: - A Master’s or Ph.D. in a specialized technical field like computer science, data science, mathematics, etc. - Experience working with sensor data (100-1KHz range) - Ability to build interactive dashboards in Hex or similar - Experience working with standard ML libraries like PyTorch, scikit-learn and basic supervised/ unsupervised learning techniques. WHY JOIN US? We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SANDBOXAQ WELCOMES ALL We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews [Upgrade to PRO to see link]