SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 170,000 - 205,000 / annual
Crusoe is a vertically integrated AI infrastructure company that owns and operates the full stack—from energy generation to cloud services—to power large-scale AI workloads. The company is solving the energy bottleneck in AI compute through an energy-first approach.
You will join Crusoe's central Data Science and Engineering team as a Senior Data Engineer, an early and pivotal hire responsible for architecting and building foundational data platform infrastructure. This is a full-time, strictly on-site role based in either the Sunnyvale or San Francisco office; remote work is not available.
Key responsibilities include:
- Architect scalable, reliable data infrastructure systems that serve as the foundation for analytics, machine learning, and operational intelligence across the company
- Build high-performance data processing frameworks and storage solutions optimized for AI infrastructure and cloud operations
- Implement data validation, monitoring, and observability systems to ensure data integrity and platform reliability at scale
- Partner with software engineers, data scientists, and operations teams to understand requirements and deliver infrastructure that accelerates their work
- Establish best practices for data engineering, contribute to architectural decisions, and mentor team members as the team grows
As an early hire on the data engineering team, you will drive projects from conception to production with significant autonomy and ownership.
REQUIREMENTS:
- Bachelor's degree (or foreign equivalent) in Computer Science, Data Engineering, Information Systems, or a closely related technical field
- Minimum 5+ years of progressive, post-baccalaureate experience in software engineering, data infrastructure engineering, or a related role
- Strong proficiency in Python and at least one systems-level language (Go preferred; Java, C, or C++ also valued)
- Deep experience designing and building data platforms, including data warehouses, data lakes, streaming systems, and ETL/ELT frameworks
- Understanding of distributed computing principles with experience building systems that scale reliably
- Advanced SQL skills for data modeling, query optimization, and database design
- Familiarity with modern DevOps practices including CI/CD, containerization, and infrastructure automation
- Ability to write production-quality, maintainable code and communicate effectively with technical and non-technical stakeholders
BONUS QUALIFICATIONS:
- Experience with Google Cloud Platform (GCP) data services (BigQuery, Dataflow, Pub/Sub, Cloud Storage)
- Experience with Apache Beam
- Background in building infrastructure for AI/ML workloads or cloud computing platforms
- Experience on a growing or early-stage data team contributing to foundational development
- Familiarity with data orchestration tools (e.g., Airflow, Dagster, Prefect)
- Experience with real-time data processing and streaming architectures
