Senior Manager, Engineering (Core Data Platform)

About the Role
We need someone who gets excited about building engineering teams that wrangle data at a scale that would make most databases cry. Not the kind of manager who just talks about "big data," but someone who understands the difference between processing millions of records and processing billions while maintaining sub-second query performance.

CloudZero's data platform is the beating heart of everything we do. We ingest billions of cost and usage events daily from AWS, Azure, GCP, and a growing list of SaaS and AI providers. When the fastest-growing engineering teams in the world throw their entire cloud spend at us, our pipelines don't flinch. When their CFOs need real-time cost attribution for board meetings, our warehouse delivers. This isn't batch processing your grandfather's ETL jobs; this is event-driven, serverless architecture that processes terabytes while customers watch.

You'll be running a team of 8 engineers who are solving legitimately hard problems: how do you build data pipelines that scale gracefully from startup to enterprise without architectural rewrites? How do you maintain data consistency across multiple cloud providers with different billing models? How do you optimize query performance when your customers' data grows by orders of magnitude?

The challenge isn't just technical. You're managing engineers who could easily land staff roles at FAANG companies, keeping them engaged on problems that push the boundaries of what's possible with modern data architecture. We've built something genuinely innovative here, but we're scaling fast.

• Architect teams for hyperscale data. Lead and grow a team of eight engineers who build the infrastructure that processes more cost data than anyone else in the industry. Your job is to create an environment where they can push the limits of data architecture without burning out.

• Drive innovation in data engineering. Champion the complex platform work that enables everything else. Help your team strike a balance between pipeline reliability and performance optimization. Make the case for architectural improvements that handle 10x growth without breaking existing systems.

• Scale data platform excellence. Design team processes that work when data volumes increase by orders of magnitude. Think through the hard engineering problems: how do you maintain data quality when ingesting from dozens of providers? How do you debug pipeline issues across distributed, event-driven systems?

• Bridge data and business. Help product teams understand data platform constraints without limiting their vision. Explain pipeline latency and storage costs to executives in terms that inform strategic decisions. Your insights should inform how we approach data architecture at scale.

• Develop data platform expertise. Help engineers level up their understanding of distributed systems, event streaming, and warehouse optimization. Create career paths for data engineers who want to work on genuinely challenging problems.
  

• You've managed data engineering teams that processed substantial volumes at companies where data pipeline failures resulted in significant business impact. You’ve done this for 5+ years at a B2B SaaS company. You may have been the person who had to explain why the warehouse was choking on a customer's data and helped the team architect a solution, not just manage the incident.

• You likely understand that great data platform engineering is about building systems that gracefully handle the unexpected. You probably have strong opinions about event streaming, warehouse design, and pipeline monitoring, but you adapt them based on actual performance characteristics.

• You might be someone who still gets excited about query optimization and data modeling but doesn't need to review every schema change. You carefully consider which architectural decisions require your input and which ones your team can own entirely.

• You can spot the difference between a pipeline that's slow because it's handling more data and one that's slow because it's poorly designed. You've likely helped engineers think through performance tradeoffs that don't have obvious answers.

• You're probably fascinated by the intersection of cloud billing data, real-time processing, and warehouse optimization. You see the potential in building data infrastructure that enables entirely new ways of thinking about cost management.

• Most importantly, you believe that data platform engineering is where the hardest and most interesting technical problems live. You see people management as the way to build systems that push the boundaries of what's possible with modern data architecture.

Please note: CloudZero is unable to sponsor employment visas. Candidates must have permanent authorization to work in the United States without the need for current or future sponsorship.