Principal Engineer (Analytics)

About Switch

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 packag