At a Glance
- Tasks: Own and evolve data foundations, build analytics features, and ensure data quality.
- 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 role with potential for growth in a rapidly evolving tech landscape.
- Why this job: Make a real impact in a fast-paced, innovative environment while shaping the future of customer support.
- Qualifications: Experience with modern analytics stacks, SQL, and building user-facing data solutions.
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 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 vibrant and supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Data Engineer
✨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 projects and data engineering prowess. This gives potential employers a taste of what you can do beyond your CV.
✨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
Some tips for your application 🫡
Show Your Passion for Data:When you're writing your application, let your enthusiasm for data engineering shine through! We want to see how you've tackled challenges in the past and how you can bring that energy to Plain. Share specific examples of projects you've worked on that relate to our mission.
Tailor Your Application:Make sure to customise your application for the Founding Data Engineer role. Highlight your experience with SQL, BigQuery, and building analytics stacks. We love seeing how your skills align with what we're looking for, so don’t hold back!
Be Clear and Concise:We appreciate straightforward communication, so keep your application clear and to the point. Avoid jargon unless it’s relevant, and make sure your key achievements stand out. This helps us quickly see how you can contribute to our team.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows 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 deep understanding of data architecture and analytics stacks. Brush up on your SQL, BigQuery, and dbt/Dataform skills, and be ready to discuss how you've built modern analytics solutions from scratch.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled data quality issues or built reusable data products in the past. Companies like Plain value initiative and impact, so highlight how your work has led to better decision-making and improved customer experiences.
✨Communicate Clearly and Effectively
Since this role involves partnering with various teams, practice articulating complex data concepts in simple terms. Be ready to explain how you can translate business questions into scalable models and datasets without getting bogged down in technical jargon.
✨Embrace Ambiguity and Greenfield Projects
Plain is looking for someone who thrives in fast-paced, evolving environments. Prepare to discuss your experience with ambiguous projects and how you've successfully navigated challenges in greenfield situations. Show them you're adaptable and ready to take ownership of new initiatives.
