At a Glance
- Tasks: Own and evolve data foundations, ensuring clean pipelines and reliable datasets.
- Company: Join Plain, a forward-thinking company redefining B2B customer support with AI.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Dynamic startup culture with a focus on innovation and collaboration.
- Why this job: Make a real impact by shaping data strategies that enhance customer relationships.
- Qualifications: Experience in building analytics stacks and strong SQL skills required.
The predicted salary is between 60000 - 80000 £ per year.
Who is Plain? Plain is redefining customer support for the next generation of B2B companies. We’re building the fastest, most powerful platform to help companies move beyond reactive support and build true customer relationships. Some of the world’s most forward-thinking companies trust Plain to unify all customer interactions, enable faster team collaboration, and supercharge their workflows with AI.
B2B customer support is undergoing a seismic shift. AI is transforming the way companies engage with customers, shifting support from a siloed function to a company-wide effort across Slack, Discord, and any other channel you talk to customers in. The old way - slow, manual, and disconnected - no longer works.
The role involves hiring a Founding Data Engineer to own and evolve Plain’s data foundations: the warehouse, core models, and the “customer/account spine” that Product, GTM, Support, and Engineering rely on to make decisions and build great experiences. This is a hands-on role. You’ll work across our data stack and partner closely with engineering teams to keep our event taxonomy, pipelines, and metrics clean as we scale.
What you'll do:
- Rebuild our data warehouse: own the architecture, schemas, and core datasets with clean pipelines and a unified event taxonomy established with Engineering.
- Deliver trusted, reusable data products: foundational datasets that power analytics, reporting, in-app features, and AI, anchored on a joinable customer/account spine across product, billing, and CS context.
- Stand up data observability: quality checks, freshness, lineage, schema drift, and incident response, so the business can trust what it sees.
- Own in-app reporting: ship the analytics features that help support leaders turn their data into better decisions.
- Enable self-serve: evolve our data layer, dashboards, and documentation so every team can run their own analysis without a ticket.
- Lay the retrieval layer behind our AI agent's customer context.
- Partner across the company: work with GTM, CX, Product, and Engineering to translate questions into scalable models and datasets.
This is a great fit if you…
- Have built modern analytics stacks end-to-end (warehouse, transformations, semantic layer, governance) from zero, ideally more than once.
- Are strong with SQL, BigQuery, and dbt/Dataform.
- Have experience building user-facing analytics or AI retrieval layers using real-time data platforms (e.g., Tinybird, ClickHouse).
- Care about data quality, trust, and reusability as much as shipping speed.
- Take initiative and measure your work by end-user impact, not elegant abstractions.
- Communicate clearly and build alignment without heavy process.
This won't be the right role if you…
- Are uncomfortable with ambiguity or greenfield work. We're early and moving fast.
- Prefer exploratory analysis over engineering reliable datasets and systems.
- Want to manage a team right now. This is an IC role.
Founding Data Engineer in London employer: Plain
At Plain, we pride ourselves on being an innovative employer that champions a collaborative and dynamic work culture. As a Founding Data Engineer, you'll have the unique opportunity to shape our data foundations while working alongside some of the brightest minds in the industry. We offer competitive benefits, a commitment to employee growth, and a chance to be part of a transformative journey in B2B customer support, all within a supportive environment that values your contributions and encourages creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at companies you admire. A casual chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your data projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining us!
We think you need these skills to ace Founding Data Engineer in London
Some tips for your application 🫡
Show Your Passion for Data:When writing your application, let us see your enthusiasm for data engineering! Share specific examples of projects you've worked on that highlight your skills in building analytics stacks and managing data quality. We love seeing candidates who are genuinely excited about the role.
Tailor Your Application:Make sure to customise your application to align with our job description. Highlight your experience with SQL, BigQuery, and any relevant tools like dbt/Dataform. This helps us see how your background fits perfectly with what we're looking for in a Founding Data Engineer.
Be Clear and Concise:We appreciate clarity! Keep your application straightforward and to the point. Use bullet points where necessary to make it easy for us to digest your experience and skills. Remember, we want to understand your impact without wading through too much fluff.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re serious about joining our team at Plain!
How to prepare for a job interview at Plain
✨Know Your Data Inside Out
As a Founding Data Engineer, you'll need to demonstrate a solid understanding of data architecture and analytics stacks. Brush up on your SQL, BigQuery, and dbt/Dataform skills. Be ready to discuss specific projects where you've built or improved data systems, focusing on the impact your work had on decision-making.
✨Showcase Your Hands-On Experience
This role is all about being hands-on, so come prepared with examples of how you've tackled real-world data challenges. Talk about how you've rebuilt data warehouses or established clean pipelines. Highlight your ability to partner with engineering teams and how you’ve ensured data quality and trust in your previous roles.
✨Communicate Clearly and Effectively
Since collaboration is key at Plain, practice articulating your thoughts clearly. Prepare to explain complex data concepts in simple terms, as you’ll need to work with various teams like GTM and Product. Think of examples where your communication helped align teams or resolve misunderstandings.
✨Embrace Ambiguity and Innovation
Plain is looking for someone who thrives in a fast-paced, ambiguous environment. Be ready to discuss how you've navigated uncertainty in past projects and turned it into an opportunity for innovation. Share your thoughts on how you can contribute to building a cutting-edge data function from the ground up.
