Sales Engineer in London

Snowplow is the real-time customer context layer that collects, validates, enriches, and delivers behavioral 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, Auto Trader, Strava, Condé Nast, and Hello Fresh, rely on Snowplow to build a well-governed, first-party data foundation that powers their customer-facing AI agents, in-session personalization and recommendations, and real-time analytics.

This Opportunity

The conversations we have with buyers have fundamentally shifted.

Instead of asking whether we can capture web and mobile events, prospects now want to know if our stream can reliably feed their live customer-facing AI agents in milliseconds without hallucinating or breaking governance.

Answering that well takes someone who understands both the data and the business problem, and who can stand in a room and connect the two.

This isn’t just a demo role.

You’ll join the Sales Engineering team and partner with Account Executives and Account Managers across the UK and EMEA.

Together you’ll set deal strategy, uncover the real problem behind each request, and guide prospects from discovery through to a decision.

You’ll work across our core behavioural data platform and our newer products, Signals and Identities, earning the trust of data leaders by leading with their priorities, not our features.

This role reports to the Director of Sales Engineering.

• What you will own
• The technical win. You partner with Account Executives throughout the sales cycle, owning discovery, solution design and the technical win.
• Discovery that finds the real problem. You ask the questions that uncover what a prospect is trying to achieve, then connect it to what Snowplow does.
• Demos that land. You tailor demonstrations to each prospect’s use case and industry, for audiences ranging from data engineers to Heads of Data and CTOs.
• Evaluations and proofs of concept. You scope them tightly, set clear success criteria with the prospect, and see them through to a decision.
• Architecture conversations. You explain how Snowplow fits alongside a prospect’s existing data warehouse, cloud platform and tooling, and advise on best practice.
• Competitive situations. You position Snowplow honestly against the alternatives a prospect is weighing up, including building it themselves.
• The voice of the field. You bring what you hear from prospects back to Product, Marketing and the wider team so we keep getting sharper.
• Reusable assets. You help build the demos, playbooks and vertical stories that the rest of the team and Sales can use.
• AI in the way we work. You use AI tools every day to work faster and smarter, and you’re often the one showing the team the next new technique.
• We would love to hear from you if you have
• Pre-sales experience in data or Saa S. You’ve worked as a Solutions Engineer, Sales Engineer, Solutions Consultant or similar, supporting a technical sale.
• Real depth in data.

You know at least one of these areas well: data warehouses (such as Snowflake, Databricks or Big Query), cloud data infrastructure on AWS, or behavioural event data.

You’re comfortable going deep in the one you know best.

• A consultative approach. You lead with questions, not slides. You know how to qualify, when to push back, and how to tie a technical answer to a business outcome.
• A track record of partnering with Sales. You’ve worked hand in hand with Account Executives, and you understand that you share the number.
• Credibility with technical buyers. Data engineers and architects trust you because you understand their world.
• Clear communication with business buyers. You can explain technical ideas in plain language to people who don’t live in the detail.
• A fast learner’s instincts. Our product and market move quickly. You pick up new technology fast and enjoy doing it.
• Comfort with ambiguity. You’re happy to work things out as you go in a growing team, and you know when to ask for help.
• Experience with streaming or real-time data (such as Kafka or Kinesis)
• Exposure to CDPs, product analytics or customer data tooling
• Python, or experience presenting analysis in notebooks
• Experience selling into retail, media, i Gaming or financial services
• What you get in return for being awesome
• Meaningful equity stake
• Generous PTO
• Private Medical Insurance
• Company Pension
• Mac Book and home office equipment allowance
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