Senior Analytics Engineer for Critical Infrastructure & AI

Switch; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Remote opportunities

Generous benefits

Job summary

Switch is seeking a Principal Engineer (Analytics) to lead engineering analytics, AI, and data platforms across its data centers. You will set technical direction, architecture, and standards for models, pipelines, and AI capabilities used to forecast power, water, and cooling system performance.

You will translate complex infrastructure data into actionable insights for capacity planning, reliability, and efficiency, while mentoring teams and guiding enterprise data governance and production

Qualifications

• Bachelor's degree required in a math-intensive discipline or equivalent.
• 10+ years across engineering, data science, or data engineering.
• 5+ years in critical infrastructure/data center environments.
• 3+ years in senior/lead architecture or standards roles.
• Strong Python and SQL, plus data engineering and ML experience.

Responsibilities

• Set direction and standards for analytics, data, and AI platforms.
• Lead evaluations and recommend analytics technologies.
• Architect data models, pipelines, and enterprise data platform.
• Develop and validate engineering models for power, cooling, and utility systems.
• Mentor engineers and align analytics with business and infrastructure needs.

Skills

Engineering analytics

Data engineering

Python

SQL

Machine learning

Leadership

Education

Bachelor's degree in Mechanical/Electrical/CS

Master's degree (preferred)

Tools

Starburst/Trino

Cloud platforms (AWS)

ETL tools

Job description

Switch is seeking a Principal Engineer (Analytics) to lead engineering analytics, AI, and data platforms across its data centers. You will set technical direction, architecture, and standards for models, pipelines, and AI capabilities used to forecast power, water, and cooling system performance.

You will translate complex infrastructure data into actionable insights for capacity planning, reliability, and efficiency, while mentoring teams and guiding enterprise data governance and production