Principal Product Manager, Platform

Job Description

The log analytics and data platform market is consolidating fast — Clickhouse, Snowflake, Databricks are all pushing into the same territory Hydrolix owns. We have the cost and performance story. What we need is someone who can turn that into a roadmap of features customers actually compare us on: enterprise authentication, self-service provisioning, MCP integration, and the infrastructure that the next generation of security and observability tooling runs on.

This role builds that roadmap and then ships it, not as a coordinator between engineering and the business, but as the person who knows the competitive landscape cold, can sit across from a prospect evaluating Clickhouse and explain exactly where Hydrolix wins and what we’re building to close the gaps, and can sequence platform investments to win more of those conversations. You’re building customer-facing capabilities that make Hydrolix a bigger force in this market.

The operational discipline this role requires — clean SDLC, cross-functional communication, metrics — serves one purpose: turning platform investments into competitive wins.

Key Responsibilities

• Collaborate on the core platform roadmap — reliability, scalability, authentication, console architecture, provisioning, and the operator experience for customers and partners, supporting the next order of magnitude of ingested data.
• Drive the platform product decisions behind ongoing strategic bets: what does it mean to make our key customer journey loops faster and easier, and how does the future of the platform reflect that priority?
• Own the platform MCP roadmap — define what Hydrolix exposes as an MCP server, how that surface evolves as agentic tooling matures, and what it means for our customers and partners to build on Hydrolix inside AI-native workflows. This includes working with engineering to sequence MCP capabilities against the roadmap and communicating the agentic platform strategy externally.
• Own ongoing competitive analysis against the vendors our customers evaluate us against — Clickhouse, Snowflake, Databricks, Elastic — and translate those findings directly into platform prioritization decisions: where we’re losing, where we’re ahead, and what we build to close the gap. This isn’t a quarterly slide deck; it’s a continuous input into sequencing.
• Implement and iterate on a cross-functional SDLC that ensures Sales Engineering and Customer Success are never learning about platform changes at the 11th hour; then improve and iterate on that process.
• Make core engineering’s work legible to the rest of the business: write the narratives that connect platform investments to customer outcomes and business metrics.
• Partner with engineering leadership on the sequencing decisions that create or enable future product options — you’re not just prioritizing a backlog, you’re making architectural bets.
• Define and track the platform metrics that matter: onboarding time, support escalation rate, operational incident volume, time-to-value for new customers and partners.

Qualifications and Skills

• Extensive experience in product management, with meaningful time on data or analytics platforms, data warehouse or transformation tooling, infrastructure, or developer/operator-facing products.
• Technical foundation strong enough to earn engineering trust — you’ve worked closely enough with distributed systems, data infrastructure, or cloud platforms to credibly provide feedback and discuss trade-offs around scope and sequencing.
• Systems thinker who sees how platform decisions today create or foreclose options for product teams building on top of them tomorrow.
• Clear, structured writer; platform work is invisible until it breaks; your job is to make it legible before that happens.
• Significant experience developing platform in an Enterprise SaaS or cloud data firm.
• Experience building the operational discipline — processes, communication rhythms, cross-functional templates — that lets an engineering-led company grow without losing coherence.
• Direct experience working inside a competing data platform is required — Clickhouse, Snowflake, Databricks, Elastic, Splunk, or a comparable log/event analytics vendor. You should be able to explain from the inside how those products make architectural decisions, where they win against us, and where they don’t.
• Experience building the platform scaffolding for AI-native workflows — MCP integration, agentic tool design, or the infrastructure layer that makes LLM applications production-ready at enterprise scale.

Bonus Qualifications

• Familiarity with cloud infrastructure, SaaS multi-tenancy, or Kubernetes-based deployments
• Experience at a company transitioning from high-touch enterprise delivery to self-service or product-led growth