Senior Data Engineer, Crusoe Energy Systems

• Strong Software Engineering Foundation: Demonstrate proficiency in Python and at least one systems-level language (Go preferred; Java, C, or C++ also valued), with the ability to write production-quality, maintainable code
• Data Infrastructure Expertise: Possess deep experience designing and building data platforms, including data warehouses, data lakes, streaming systems, and ETL/ELT frameworks
• Distributed Systems Knowledge: Show understanding of distributed computing principles, with experience building systems that scale reliably
• SQL Mastery: Exhibit advanced SQL skills for data modeling, query optimization, and database design
• Infrastructure-as-Code Mindset: Demonstrate familiarity with modern DevOps practices including CI/CD, containerization, and infrastructure automation
• Ownership & Autonomy: As an early hire on the data engineering team, you'll be expected to drive projects from conception to production with minimal supervision
• Collaboration Skills: Communicate effectively with technical and non-technical stakeholders to translate requirements into robust solutions

Desirable

• Join Crusoe Energy as a Senior Data Engineer, an early and pivotal hire on our growing central Data Science and Engineering team
• This full-time position offers you the unique opportunity to architect and build the foundational data platform infrastructure that powers Crusoe's AI and cloud operations
• You'll go beyond building pipelines—you'll design and implement the systems that make those pipelines possible, playing a key role in Crusoe's mission to meet the ever-increasing demand for AI infrastructure and innovate sustainably
• Architect Data Platform Infrastructure: Design and build scalable, reliable data infrastructure systems that serve as the foundation for analytics, machine learning, and operational intelligence across Crusoe
• Build High-Performance Data Systems: Develop robust data processing frameworks and storage solutions optimized for the unique demands of AI infrastructure and cloud operations
• Champion Data Quality & Reliability: Implement data validation, monitoring, and observability systems that ensure data integrity and platform reliability at scale
• Collaborate Across Engineering Teams: Partner with software engineers, data scientists, and operations teams to understand requirements and deliver infrastructure that accelerates their work
• Drive Technical Excellence: Establish best practices for data engineering, contribute to architectural decisions, and mentor team members as the team grows