Senior Software Engineer, Data Platform

Join Crusoe Energy as a Senior Data Engineer, an early and pivotal hire on our growing central Data Science and Engineering team. This is a full-time, strictly on-site role based out of our Sunnyvale, CA or San Francisco office; remote work arrangements are not eligible for this position. 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.

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.

Minimum Educational Requirement: Bachelor’s degree (or foreign equivalent) in Computer Science, Data Engineering, Information Systems, or a closely related technical field.

Minimum Experience: 5+ years of progressive, post-baccalaureate experience in software engineering, data infrastructure engineering, or a related role.

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.