Principal Engineer (Analytics)

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

At Switch, we don't just design, build and operate data centers-we are enabling the technology of the future. Led by Founder & CEO, Rob Roy, we believe in revolutionary innovation, operational excellence and the principle of karma. Switch is where talented people come together to EVOLVE the digital world.

We believe that innovation isn't just about technology-it's about the people, culture, and purpose that make it happen. Every Switch team member contributes to a mission greater than themselves: to create the world's most advanced digital infrastructure that powers the progress of humanity.

The Role: Principal Engineer (Analytics)

The Principal Engineer (Analytics) serves as a senior technical authority for engineering analytics, AI, and data platforms supporting critical infrastructure across Switch data centers. This role sets technical direction, architecture, and engineering standards for the models, data pipelines, analytical platforms, and AI capabilities used to understand and forecast power, water, and cooling system performance.

You will translate complex infrastructure behavior and operational data into defensible engineering and business insights that support utility resourcing and power procurement, capacity management, energy and water efficiency, reliability-centered and condition-based maintenance, root cause analysis, design feedback, end-of-life planning, and other infrastructure lifecycle programs.

As a Principal Engineer, you will establish technical standards, solve the most complex analytical and engineering problems, and influence decisions across Availability Engineering, Operations, Reliability, Controls, Commissioning, Construction, Design, Finance, and IT. You will also raise technical capability across the organization through architecture reviews, technical guidance, mentorship, and engineering standards.

What You’ll Do

• Set the technical direction, target-state architecture, roadmap, and engineering standards for Switch’s engineering analytics, data, and AI platforms.
• Lead build-versus-buy evaluations and provide defensible technical and financial recommendations for analytical technologies and platforms.
• Establish enterprise data architecture, models, schemas, and ETL/ELT patterns on the Switch Data Platform, including Starburst.
• Ensure pipelines integrating controls, CMMS, Finance, and other enterprise data sources are scalable, governed, reusable, and appropriate for production use.
• Architect and validate first-principles and data-driven engineering models for power, water, and cooling infrastructure.
• Develop and establish standards for energy balance, thermodynamic, forecasting, reliability, and other engineering and statistical models.
• Establish model validation, versioning, uncertainty, and documentation standards so analytical outputs are defensible for Engineering, Finance, Procurement, Operations, and executive decision-making.
• Define data-quality standards, monitoring requirements, and remediation processes across engineering analytics systems.
• Identify telemetry, instrumentation, and points-list gaps and partner with Controls and Operations to improve data fidelity.
• Set technical direction for machine learning, generative AI, and agentic capabilities supporting diagnostics, predictive maintenance, engineering analysis, and workflow automation.
• Evaluate emerging AI technologies and determine where they can be applied safely and effectively to engineering and operational problems.
• Establish governance for AI-assisted development, model risk, approved tooling, and production use.
• Set standards for production readiness, observability, access control, security, scalability, and data protection across analytics systems and applications.
• Own technical risk for business-critical analytical models, pipelines, and engineering data products.
• Lead architecture, design, and code reviews for complex analytics and data engineering solutions.
• Serve as an escalation point for the organization’s most complex engineering analytics, data, and modeling problems.
• Mentor engineers, analysts, and other technical contributors and strengthen engineering practices across the team.
• Partner with Operations, Reliability, Controls, Commissioning, Construction, Design, Finance, and IT leadership to align analytics priorities with business and infrastructure needs.
• Translate complex engineering and analytical findings into clear recommendations for technical, business, and executive audiences.
• Use engineering analytics to support capacity planning, infrastructure reliability, energy and water efficiency, lifecycle planning, root cause analysis, and continuous improvement.
• Provide technical and analytical guidance that informs infrastructure design, capital planning, procurement, operational practices, and executive decisions.

What We’re Looking For

• You establish technical direction and standards for complex engineering and analytical systems.
• You combine deep infrastructure engineering knowledge with expertise in data engineering, statistical analysis, modeling, and AI.
• You solve ambiguous problems that span multiple technical systems, functions, and business priorities.
• You use first-principles engineering, statistical methods, and operational data to develop defensible conclusions.
• You understand the limitations and uncertainty in analytical models and communicate those limitations clearly when decisions depend on them.
• You translate complex technical findings into clear business implications and recommendations.
• You influence engineering and business decisions through technical expertise and credibility rather than formal authority.
• You establish reusable architectures and standards rather than solving the same problem independently for each project.
• You identify systemic data, telemetry, modeling, or infrastructure issues and drive improvements across teams.
• You evaluate emerging technologies based on practical engineering value, risk, scalability, and business impact.
• You mentor technical talent and raise engineering practices across the organization.
• You remain effective when information is incomplete, requirements are evolving, or decisions carry significant operational or business impact.

What You’ll Bring

Required Qualifications

• Bachelor of Science in Mechanical Engineering, Electrical Engineering, Computer Science, or an equivalent math-intensive discipline.
• 10+ years of combined experience across engineering, data science, data engineering, or closely related technical disciplines.
• 5+ years of experience supporting critical infrastructure or data center operations.
• 5+ years of experience in data science, data engineering, engineering analytics, or a comparable analytical role.
• 3+ years in a senior or lead technical role with responsibility for architecture, technical direction, or engineering standards.
• Expert understanding of electrical and mechanical systems used in data center environments, including electrical feeders, transformers, generators, switchgear, UPS systems, power systems, ATS/STS units, PDU units, air handling units, cooling towers, pumping systems, and fire suppression systems.
• Understanding of how critical electrical and mechanical systems interact during normal, degraded, and failure conditions.
• Ability to interpret P&IDs, wiring diagrams, schematics, sequences of operation, submittals, and MEP drawing packages.
• Expert knowledge of data engineering, statistical methods, and engineering modeling.
• Strong understanding of thermodynamics, heat transfer, time-series forecasting, and related engineering analytical methods.
• Demonstrated experience architecting and delivering complex, multi-system data and analytics platforms in production.
• Advanced proficiency with Python and SQL.
• Experience with distributed query engines such as Starburst/Trino.
• Experience with data pipeline orchestration, version control, and cloud computing platforms.
• Experience with machine-learning frameworks and AI/LLM application development tools.
• Demonstrated experience establishing technical strategy and advising senior leadership.
• Ability to resolve ambiguous, cross-functional technical problems and drive them to measurable outcomes.
• Strong written and verbal communication skills with the ability to translate technical analysis into business impact.

Preferred Qualifications

• Master’s degree in Mechanical Engineering, Electrical Engineering, Computer Science, Data Science, or another relevant quantitative discipline.
• Professional Engineer (PE) license.
• Experience establishing enterprise data architecture or engineering analytics standards.
• Experience developing first-principles and data-driven models for mission-critical infrastructure.
• Experience supporting utility resourcing, power procurement, capacity planning, PUE/WUE analysis, reliability programs, condition-based maintenance, or infrastructure lifecycle planning.
• Experience developing or governing generative AI, machine-learning, or agentic solutions in production environments.
• Experience providing technical leadership across geographically distributed data center or critical infrastructure environments.

We recognize that qualified candidates may not meet every preferred qualification. If your experience aligns with the core responsibilities of the role, we encourage you to apply.

Why Switch?

A Culture of Karma – We are self-motivated by karma, ensuring our actions contribute to a positive, supportive and forward-thinking environment.

Industry Leading Designs – Work with the most advanced data center technology on the planet and be a part of emerging technology development.

Flexibility & Remote Opportunities – Whether in-office, hybrid, or fully remote, we offer the technology and support to keep teams connected and productive.

Career Stability & Growth – In this expanding industry, we invest in our people, providing opportunities & advancement in a stable, growing company.

Generous Benefits Package - Switch provides comprehensive coverage for you and your family that can be tailored to fit your personal needs, and more!

Join Us & Make a Difference

This is more than a job—it’s a mission. If you’re ready to be part of a culture that values innovation, karma, and limitless potential, we want to hear from you.

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