Principal Product Manager — Analytics

About Snowplow

Snowplow is the real-time customer context layer that collects, validates, enriches, and delivers behavioural data for advanced analytics, ML, and AI agent decisioning. Snowplow's event tracking is leveraged across 2M+ websites and applications globally, processing over one trillion events per month.

More than 250 companies, including Experian, AutoTrader, Strava, Condé Nast, and HelloFresh, rely on Snowplow to build a well-governed, first-party data foundation that powers their customer-facing AI agents, in-session personalisation and recommendations, and real-time analytics.

The Opportunity

We're hiring a Principal Product Manager to own and set the strategic agenda for Snowplow's analytics offerings, spanning our packaged analytics data models (what we call data model packs and the next generation of AI-native, natural-language access to behavioral data. This is a significant and growing part of our business, and this role exists to give it one clear owner driving strategy and roadmap. This isn't a stewardship role. Over the next few years we expect this line to evolve from batch data model packs into a real-time streaming analytics engine, built on a canonical ontology of digital journeys that both humans and AI agents can reason over.

Reporting to the CPO, this is a senior individual-contributor role, built for someone who drives strategy and roadmap through influence and credibility rather than headcount. You'll hold full ownership of product strategy, roadmap, and external narrative for this line. You'll partner closely with engineering and product marketing to turn strategy into shipped product, and you'll be the person customers, partners, and internal stakeholders look to for where the next generation of analytics at Snowplow is headed.

This role is about making sure the behavioral data we collect is legible and valuable on its own terms, for both humans and AI agents. We want it to be simple for people and agents at our enterprise customers to author rich behavioral data, describing the behavior of both people and agents, and for the resulting data to be immediately and unambiguously understandable, by humans and by the AI agents acting on their behalf. That understanding needs to support multiple analytics workloads: product analytics, where agents increasingly drive the software development lifecycle itself, and customer analytics, spanning acquisition, retention, and growth across marketing and customer success. That spans three frontiers: evolving our data model packs beyond batch into streaming computation, defining the ontology of digital journeys (the entities, events, and relationships that describe how people and agents move through digital products), and connecting Snowplow's semantics to open standards like Apache Ossie so they travel with the data into any BI tool or agent. You'll be picking up real momentum and products already in flight and shaping it into a coherent, prioritized strategy.

Why now

AI has changed whose behavior we track. It's no longer just people; it's agents acting on behalf of customers, suppliers, partners, and competitors. AI has also changed how analysis itself gets done: agents are increasingly the primary consumers of analytical data, not just the humans reading a dashboard. At the same time, AI has dramatically increased our own development velocity, so whoever takes this role has a real chance to realize a much more ambitious vision, and realize it far faster than would have been possible even a year ago.

What you will be doing

• Set product strategy and own the roadmap for Snowplow's analytics offerings, including data model packs and emerging semantic layer / agentic analytics capabilities.

• Lead the evolution of our data model packs from batch models into a real-time streaming engine, so journey analytics are computed in-stream rather than hours later.

• Define and publish Snowplow's ontology of digital journeys, and make it the semantic backbone of our packs, interfaces, and agent integrations.

• Define our point of view on how customers and their AI agents should query and reason over behavioral data, and prioritize the roadmap accordingly.

• Own our approach to distinguishing human from AI agent and bot traffic, an increasingly important part of trustworthy analytics as agentic traffic grows.

• Make and defend build vs. partner decisions involving the broader data and AI ecosystem (warehouse platforms, semantic layer standards, natural-language analytics tools).

• Partner with engineering and product marketing to move initiatives from concept to shipped, adopted product.

• Work cross-functionally with sales, marketing, and customer success to ensure this part of the product is well positioned, well understood, and easy to sell.

• Represent this product line externally with customers, prospects, and technology partners.

• Communicate strategy clearly to company leadership, translating complex product thinking into concise, decision-ready materials.

We would love to hear from you if you have

• Proven product management experience, with a track record of building and scaling a commercial product offering sold to external customers, not an internal-only tool or platform.

• A product analytics background: someone who's built or scaled a product analytics offering and has a point of view on where the category is going, particularly around natural-language / agentic interfaces to data.

• Proven ability to operate as a single-threaded owner with no direct reports; you drive outcomes through influence, clarity, and credibility, not headcount.

• Comfort making and defending build/partner decisions involving warehouse-native ecosystems (Databricks Genie, Snowflake Cortex, dbt, Unity Catalog) and open semantic standards (Apache Ossie).

• Strong technical fluency: you can go deep enough on semantic layers, data modeling, and enrichment pipelines to have a real conversation with engineering, without needing to own the implementation.

• A track record of turning ambiguous, multi-workstream backlogs into a single coherent strategy: this role starts with multiple active workstreams and no unifying plan.

• Executive presence: you can walk into a leadership or board conversation and land a point simply, directly, and with a clear recommendation.

What you get in return for being awesome

• Meaningful equity stake

• Competitive Base Salary

• Flexible working

• Generous PTO

• Private Medical Insurance

• Company Pension

• MacBook and home office equipment allowance

• Enhanced Family leave

Originally posted on Himalayas