Sr. Analytics Engineer-Product Insights

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.

About the Role:

We're hiring a Product Analytics Engineer for CrowdStrike's Product Insights team. Our team designs, builds, and maintains the analytics data systems that power the award-winning Falcon Console. This work is foundational; it enables fast, accurate, data-driven decision-making that keeps customers raving about our products.

As a Product Analytics Engineer, you'll build data systems that deliver actionable insights on how users interact with our products and services. You'll capture, transform, and integrate data from multiple sources into a unified analytics platform, all while working with a team that's innovating to protect customers from increasingly complex threat actors. This role requires navigating ambiguity and undefined problem spaces, working across multiple product groups and disciplines to drive impact.

We build teams of technically strong people who make each other better. That means bringing sharp skills while staying curious and humble, and genuinely caring about the growth and success of those around you. If you love exchanging ideas and are as invested in your teammates' wins as your own, this is the place for you.

Who You Are:

We want someone with technical skills and the right mindset:

• A self-starter who wants to grow and learn

• You make choices based on data and good judgment

• You lead by helping others and sharing knowledge

• You work well with others and get people aligned

• You adapt when priorities change

• You do the right thing for colleagues and users

• You use AI tools to work faster

What You'll Do:

• Design and build our data systems and analytics tools

• Deliver accurate insights that drive business choices and product decisions

• Balance several projects at once and tell stakeholders about trade-offs

• Build data pipelines that process large amounts of data

• Use AI tools daily and share how you use them with the team

• Ask smart questions and shape outcomes, not just do tasks

• Own your work and make sure it succeeds

What You'll Need:

Required:

• Bachelor's degree in Computer Science, Engineering, Math, Statistics, or related field (or equal work experience)

• Strong programming skills in at least one modern language (Python, Go, or similar)

• Deep SQL expertise and hands-on experience with modern data platforms (RDBMS, NoSQL, or Graph databases)

• You can design systems for moving and changing data at scale using tools like Kubernetes and Docker

• Experience with cloud infrastructure (AWS, GCP, OCI, or Azure)

• Strong data visualization and storytelling skills; you can construct concise, coherent narratives supported by appropriate visualizations using BI tools such as Tableau, Looker, Power BI, or similar platforms

• A thorough understanding of engineering best practices - from testing paradigms to peer code reviews and resilient architecture design

• Excellent communic