At a Glance
- Tasks: Design and build a cutting-edge internal data platform from scratch.
- Company: Join Fonoa, a forward-thinking tech company focused on solving real customer problems.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Embrace the challenge of building something new and impactful.
- Why this job: Be part of an innovative team that values ownership and collaboration in a dynamic environment.
- Qualifications: 5+ years in Data Engineering, strong SQL skills, and experience with modern data tools.
The predicted salary is between 60000 - 80000 £ per year.
About Engineering At Fonoa Engineering is central to how we build the business. We focus on solving real customer problems, not just shipping features. We work in small, high-trust teams, with full ownership across the lifecycle, from design to production and beyond.
We value:
- Ownership – engineers own what they build end-to-end
- Simplicity – we break down complex problems into clear solutions
- Thinking Big - we innovate with modern technologies (LLMs, AI Agents, etc.) to solve meaningful problems
- Quality – scalable, maintainable systems are non-negotiable
- Speed & iteration – we ship fast, learn, and improve continuously
- Collaboration – we win as a team, not as individuals
Position Overview As Fonoa continues to scale globally, we are looking for a Data Engineer to help us bootstrap an internal data platform from the ground up. Working closely with the Infrastructure team, you will play a foundational role in unlocking the value hidden across our different systems and make data accessible to both technical and non‑technical stakeholders in a seamless way. This is not a role where you'll walk into a mature data stack with well‑defined requirements. We have data spread across multiple systems and services, and we need someone who can help us experiment, iterate, and discover how to best add value to the business and our products through data. You'll be exploring what's possible, building the first versions of pipelines and tooling, and shaping the direction of data engineering at Fonoa. This is a highly collaborative, hands‑on role for someone who thrives in ambiguity, brings curiosity and proactivity, and is energised by the challenge of building something from scratch rather than maintaining something that already exists.
What Will You Do
- Data Platform Foundations
- Design, build, and iterate on the foundational data infrastructure that will become Fonoa's internal data platform
- Evaluate and select appropriate tools and technologies based on our needs, scale, and team capabilities
- Establish patterns and best practices for data modelling, cataloguing, and documentation, and data governance and quality standards early on
- Data Integration & Access
- Connect and consolidate data from multiple internal systems and services into a unified, queryable layer
- Build interfaces and tooling that enable non‑technical users (including Product, Finance, Operations) to consume data independently
- Ensure data quality, consistency, and reliability across sources through validation and monitoring
- Exploration & Value Discovery
- Partner with stakeholders across the business to understand their data needs and identify high‑impact opportunities
- Prototype dashboards, reports, and data products to test hypotheses about where data can drive decisions
- Help define what "data‑driven" looks like at Fonoa and shape the roadmap accordingly
- Collaboration & Enablement
- Work closely with the Infrastructure team on cloud resources, networking, and security considerations for data workloads
- Partner with Finance, Operations, and Product to understand their reporting and analytical needs, and translate those into reliable, queryable data products
- Share knowledge and advocate for data engineering best practices across the organisation
What We Are Looking For
- 5+ years of experience in a Data Engineering or similar role (Analytics Engineering, Backend Engineering with heavy data work)
- Solid proficiency in SQL and at least one programming language (Python, Scala, or similar)
- Experience building and maintaining ETL/ELT pipelines and working with data warehousing or lakehouse architectures
- Hands‑on experience with modern data stack tooling — particularly a columnar warehouse (BigQuery, Snowflake, or similar), a transformation layer (dbt or equivalent), and an ingestion/CDC tool (Airbyte, Fivetran, or similar)
- Familiarity with cloud platforms (GCP preferred) and their data services
- Experience with workflow orchestration tools
- Strong communication skills and the ability to work with non‑technical stakeholders and translate their needs into data solutions
- Comfort with ambiguity and an ability to make pragmatic decisions with incomplete information
- Prior experience bootstrapping a data platform or data function from scratch
Bonus Points If You Have
- Experience with data visualisation and BI tools (Metabase, Looker, Superset, or similar)
- Background working in a product‑oriented SaaS company
- Experience working with financial or operational data (revenue, billing, reconciliation)
- Exposure to infrastructure‑as‑code and DevOps practices
What Success Looks Like
- A first iteration of an internal data platform is running, consolidating data from key systems into a reliable, queryable layer
- Non‑technical stakeholders can access and explore data relevant to their work without needing engineering support for every question
- Clear patterns and documentation exist for how data is ingested, transformed, and consumed
- You have identified and delivered at least one high‑impact data use case that demonstrably adds value to the business or product
Tech Stack We use these technologies today, but we don’t hire for specific tools. We care about engineers who can understand problems, make good technical decisions, and choose the right tools for the job.
- Backend: Node.js, Go
- Frontend: React, TypeScript
- Infrastructure: GCP, k8s, Terraform, Postgres
Additional Information If you don’t think you have the full experience we’re looking for, but you could be a fit and are willing to learn, do apply anyway! We are building a diverse and inclusive team.
Senior/Staff Data Engineer employer: Fonoa
Fonoa is an exceptional employer that fosters a dynamic startup atmosphere, offering employees the chance to grow and innovate within a diverse tech environment. With a strong focus on enhancing internal IT processes and supporting a distributed team, Fonoa provides meaningful work, opportunities for professional development, and a culture that values collaboration and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Senior/Staff Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Fonoa on LinkedIn or other platforms. Ask them about their experiences and the company culture. This not only shows your interest but can also give you insider info that might help you stand out in interviews.
✨Tip Number 2
Prepare for technical interviews by brushing up on your SQL and programming skills. Practice common data engineering problems and be ready to discuss your past projects. We want to see how you think and solve problems, so be ready to showcase your thought process!
✨Tip Number 3
Showcase your curiosity! During interviews, ask insightful questions about Fonoa's data challenges and how you can contribute. This demonstrates your proactive mindset and aligns with our value of thinking big and innovating with modern technologies.
✨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, it shows you’re serious about joining our team and building something amazing together.
We think you need these skills to ace Senior/Staff Data Engineer
Some tips for your application 🫡
Show Your Ownership:When writing your application, make sure to highlight your experience with end-to-end ownership of projects. We love engineers who take pride in what they build and can demonstrate how they've tackled complex problems from start to finish.
Keep It Simple:We appreciate clarity! Use straightforward language to explain your skills and experiences. Avoid jargon where possible, and focus on how you’ve broken down complex data challenges into simple, effective solutions.
Think Big:Don’t shy away from showcasing your innovative side. Share examples of how you've used modern technologies or creative approaches to solve meaningful problems in your previous roles. We want to see your big ideas!
Collaborate and Communicate:Since collaboration is key for us, mention any experiences where you've worked closely with non-technical stakeholders. Highlight your ability to translate their needs into actionable data solutions, as this will resonate well with our team culture.
How to prepare for a job interview at Fonoa
✨Understand the Company Culture
Before your interview, take some time to research Fonoa's culture and values. They focus on ownership, simplicity, and collaboration, so think about how your experiences align with these principles. Be ready to share examples that demonstrate your ability to work in high-trust teams and tackle complex problems.
✨Showcase Your Technical Skills
As a Senior/Staff Data Engineer, you'll need to highlight your proficiency in SQL and programming languages like Python or Scala. Prepare to discuss your experience with ETL/ELT pipelines and modern data stack tools. Bring specific examples of projects where you’ve built or maintained data infrastructure, as this will show your hands-on experience.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to handle ambiguity and make decisions with incomplete information. Think of scenarios where you've had to experiment and iterate to find solutions. This role is about building from scratch, so be ready to discuss how you approach problem-solving in uncertain situations.
✨Engage with Stakeholders
Fonoa values collaboration across departments, so be prepared to talk about how you've worked with non-technical stakeholders in the past. Share examples of how you translated their needs into data solutions, and demonstrate your strong communication skills. This will show that you can bridge the gap between technical and non-technical teams.
