Principal Software Engineer, Data Analytics

Principal Software Engineer, Data Analytics

Tacoma, Washington, United States and 2 more

At Infoblox, every breakthrough begins with a bold “what if.”
What if your ideas could ignite global innovation?
What if your curiosity could redefine the future?

We invite you to step into the next exciting chapter of your career journey. Bring your creativity, drive, your daring spirit, and feel what it’s like to thrive on a team big enough to make an impact, yet small enough to make a difference. Our cloud-first networking and security solutions already protect 70% of the Fortune 500
, and we’re looking for creative thinkers ready to push that influence even further. Join us and discover how far your bold “what if” can take the world, your community, and your career.

Here, how we empower our people is extraordinary:
Glassdoor Best Places to Work 2025, Great Place to Work-Certified in five countries, and Cigna Healthy Workforce honors three years running — and what we build is world-class: recognized as Cybersec Asia’s Best in Critical Infrastructure 2024
—evidence that when first-class technology meets empowered talent, remarkable careers take shape. So,
what if the next big idea, and the next great career story, comes from you? Become the force that turns every “what if” into “what’s next”.

In a world where you can be anything,
Be Infoblox
.

Principal Engineer, Data Analytics

We have an opportunity for aPrincipal Engineer to join ourData & AIteam in North America,reporting tothe VP of Data & AI. In this pivotal role, you willdrive the design and delivery of intelligent, AI-powered systems that transform data into actionable insights and automated decision-making. This role will shape the architecture for closed-loop, intent-driven analytics platforms that deliver predictive and prescriptive outcomes across Infoblox’s product ecosystem.

The ideal candidate is self-driven, thrives in ambiguity, and leads with influence across Product, Data Science, and Engineering to deliver measurable business outcomes.

Be a Contributor — What You’ll Do

• Architect and lead architecture and implementation of a greenfield AI analytics product, from proof of concept to production launch, aligning technical decisions to business outcomes.
• Collaborate with data engineering, data science, and product teams to develop closed-loop systems that continuously learn and adapt from feedback signals.
• Integrate predictive and prescriptive analytics models into production systems, enabling automated recommendations and self-optimizing decisions.
• Define and implement data-to-action architectures, leveraging AI/ML, event-driven designs, and microservices to create real-time decisioning capabilities.
• Champion observability, reliability, and explainability as core principles in all analytics systems—ensuring outputs are measurable, transparent, and trustworthy.
• Drive engineering excellence through architecture reviews, mentoring, and cross-functional alignment, influencing teams toward unified analytics and automation standards.
• Partner with product leaders to define KPIs and success metrics that measure the business impact of analytics and automation.
• Drive engineering best practices and platform patterns (CI/CD, IaC with Terraform/Cloud Formation, SDLC quality gates, SLOs, runbooks) across collaborating teams.

Be Prepared — What You Bring

• 15+ years of professional software engineering experience, with 5+ years building or leading large-scale cloud or analytics platforms.
• Expertise in Python, Go, or Java, with strong fundamentals in distributed systems, data structures, and algorithms.
• Strong command of cloud-native architecture patterns—microservices, containers (EKS/Kubernetes), event-driven design, and zero-trust security.
• Demonstrated ability to lead with influence—driving clarity, alignment, and outcomes across product, data science, and platform teams.
• Self‑driven ownership mindset with a track record of delivering complex systems from concept to production, balancing agility, reliability, and cost.
• Understanding of streaming and event-based systems, telemetry, and feedback loops for continuous learning.
• Demonstrated success in building…