Solutions Architect

About Snowplow

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, 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 personalization and recommendations, and real-time analytics.

This Opportunity

Our customers no longer use behavioural data only for dashboards. They now feed it into recommendation engines, in-session personalisation, and customer-facing AI agents. That means the data has to be governed, real-time, and trustworthy from the first event, and it raises the bar for how every Snowplow deployment is designed.

As a Solutions Architect in our Technical Services team, you'll lead the technical side of each customer's journey with Snowplow, from first implementation to their long-term roadmap. Implementation is the heart of the job: you'll design tracking, pipelines, and data models across our platform. But the work doesn't end at go-live. You'll stay with a portfolio of customers as their technical partner, helping them solve new problems, take on new use cases, and get more value from their data over time.

You'll work alongside Customer Success, Account Management, Support, Product, and Engineering, and what you learn and build in the field will help shape our product and strategy. You'll be hands-on with schemas, trackers, SQL, JavaScript, and more, and you'll be trusted to help customers make critical decisions and design choices.

What you will own

Implementation

• Customer implementations, end to end. Lead the technical side of new customer onboardings, from the Sales handover to a production pipeline the customer trusts.
• Tracking design that answers real questions. Help customers build tracking plans and schemas that reflect what the business needs to know.
• Data modelling. Guide customers from raw events to analytics-ready tables, using our packages alongside customers’ own models.
• Real-time and AI use cases. Help customers build real-time solutions driven by Snowplow Signals, from proof of concept to production.

Long-term technical partnership

• A portfolio of customers. Be the ongoing technical lead for a set of accounts, building relationships with their data teams that outlast any single project.
• Consultative advice. Help customers shape their data strategy and use-case roadmap through tailored workshops and advisory sessions.
• Solving complex problems. Work with customers and our Support team to diagnose and resolve issues across front-end tracking, data modelling, and real-time processing.
• Adoption and growth. Partner with Customer Success and Account Management on long-term adoption roadmaps, and spot where customers can get more from Snowplow.
• Field insight and reusable assets. Bring what you learn back to Product and Engineering, and build the data models, reference architectures, and field code that make every engagement faster than the last.

We would love to hear from you if you have

• Customer-facing technical experience. Several years in solutions architecture, technical account management, technical consulting, sales engineering, or professional services, ideally at a data or SaaS company.
• A consultative approach. You ask the right questions before proposing a solution, and you're comfortable advising senior technical stakeholders such as CTOs, Heads of Data, and tech leads.
• Long-term customer relationships. You've looked after customers or accounts over time, not only through one-off projects.
• Solid data engineering foundations. You understand how data moves from collection to the warehouse, and you've built or supported pipelines that do it.
• Comfort in code. You can use Python or JavaScript to debug a tracker implementation, build a demo, or help colleagues and customers build field solutions.
• Clear communication. You can explain a schema decision to an engineer and its business impact to a data leader in the same meeting.
• Ownership across many priorities. You balance implementation deadlines with ongoing account needs, prioritise well, and follow through without being chased.

Bonus points for

• Experience with Snowplow or other behavioural data and event tracking tools.
• Hands-on experience with dbt.
• Experience with streaming platforms such as Kafka, Kinesis, or Pub/Sub.
• Exposure to ML or AI use cases, such as feature engineering or personalisation.
• Familiarity with data governance, privacy, and consent requirements such as GDPR.

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