At a Glance
- Tasks: Build and scale data infrastructure for a fast-growing creator monetisation platform.
- Company: Join Fanvue, a leading AI-powered platform transforming the creator economy.
- Benefits: Enjoy remote work, flexible hours, unlimited holiday, and a budget for growth.
- Other info: Diverse teams welcome; we value potential and ambition just as much as experience.
- Why this job: Shape the data foundation of a $100M+ ARR platform and enable advanced analytics.
- Qualifications: 5+ years as a data engineer with strong AWS and dbt expertise.
The predicted salary is between 70000 - 90000 £ per year.
Join us in redefining the creator economy with AIFanvue, one of the fastest-growing creator monetisation platforms globally. We’re an AI-powered, creator-first platform helping creators connect, engage, and earn directly from their audiences at scale. Following our recent Series A, Fanvue has surpassed $100M+ in annual recurring revenue, with triple-digit year-on-year growth, supporting hundreds of thousands of creators and millions of fans worldwide.
As Fanvue scales, data is becoming a critical execution layer across product, growth, finance, and risk. This role exists to build a production-grade data foundation that the entire company can trust, unlocking faster decision-making, advanced analytics, and machine learning capabilities at scale.
The RoleWe’re hiring a Senior Data Engineer to own and scale Fanvue’s core data infrastructure. This is a foundational, high-leverage role. You will be responsible for stabilising data ingestion, improving observability and governance, reducing manual toil, and enabling advanced analytics and machine learning workloads. Your work will directly underpin Fanvue’s ability to operate as a truly data-driven organisation.
What You’ll Do- Own and stabilise end-to-end data ingestion pipelines, including CDC ingestion via Amazon DMS.
- Resolve schema drift issues and automate column ingestion to eliminate manual re-syncs.
- Build production-grade observability for data pipelines, dbt runs, and Athena performance.
- Implement monitoring and alerting to proactively detect data quality or pipeline failures.
- Optimise CI/CD workflows for data transformations, reducing PR build times and deployment friction.
- Design and implement reusable ingestion frameworks for rapid onboarding of new data sources.
- Establish strong data governance practices, including dbt tests in production and scheduled full-refresh pipelines.
- Enable advanced analytics and ML infrastructure, including AWS SageMaker integration and ad-hoc analytics environments.
- Implement fine-grained access controls (RBAC) to protect PII and sensitive data as the company scales.
- Own Infrastructure as Code for the data platform using AWS CDK, ensuring data infrastructure is versioned, testable, and reproducible.
- Collaborate closely with Platform, Analytics, and Product teams to align data infrastructure with business needs.
- 5+ years of experience as a data engineer building production-grade data pipelines.
- Deep hands-on experience with AWS data services such as S3, Athena, Glue, DMS, and CodePipeline.
- Strong dbt expertise, including deployment architecture, CI/CD integration, and performance optimisation.
- Proven experience implementing data quality frameworks, observability, and governance at scale.
- Solid Infrastructure as Code mindset, with experience using AWS CDK (TypeScript preferred). Terraform experience is acceptable if you are willing to adopt CDK.
- Comfortable designing scalable data architectures and reusable ingestion patterns.
- Strong ownership mindset, able to diagnose and resolve complex infrastructure issues independently.
- Confident collaborating across analytics, platform, and product teams to deliver shared outcomes.
- You enjoy building reliable systems that other teams depend on.
- You care deeply about data quality, trust, and production readiness.
- You like turning fragile pipelines into boring, predictable infrastructure.
- You are motivated by leverage and long-term impact, not quick hacks.
- You believe speed and reliability can and should coexist.
- You prefer exploratory analytics over production-grade infrastructure.
- You are uncomfortable owning critical systems end to end.
- You rely on manual fixes instead of automation and observability.
- You avoid accountability for reliability, data quality, or platform health.
- Own and shape the data foundation of a $100M+ ARR platform.
- Enable advanced analytics and machine learning across the business.
- High autonomy with clear ownership and impact.
- Work closely with Platform, Analytics, and Product leadership.
- Remote working.
- Flexible hours, according to when you perform best.
- Unlimited holiday.
- Budget for growth and wellbeing.
- A culture that values innovation, ownership, transparency, and speed.
We know that diverse teams build better companies. Even if you do not meet every single requirement, we encourage you to apply. Many great people grow into parts of a role, and we value potential, mindset, and ambition just as much as experience.
Senior Data Engineer employer: Fanvue LLC
Contact Detail:
Fanvue LLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Fanvue on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your application noticed.
✨Tip Number 2
Show off your skills in action! If you have a portfolio or GitHub with relevant projects, make sure to highlight them during interviews. It’s a great way to demonstrate your expertise in building data pipelines.
✨Tip Number 3
Prepare for technical challenges! Brush up on AWS services and data governance practices. Being ready to tackle real-world problems will impress the hiring team and show you’re the right fit for the role.
✨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 genuinely interested in joining the Fanvue team.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Engineer role. Highlight your hands-on experience with AWS data services and any relevant projects that showcase your ability to build production-grade data pipelines.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to Fanvue's mission. Share specific examples of how you've improved data quality or implemented observability in past roles.
Showcase Your Problem-Solving Skills: In your application, don't shy away from discussing complex infrastructure issues you've tackled. We love candidates who can demonstrate their ownership mindset and ability to resolve challenges independently.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Fanvue LLC
✨Know Your Data Tools Inside Out
Make sure you’re well-versed in AWS data services like S3, Athena, and Glue. Brush up on your dbt expertise too, as they’ll likely ask you about deployment architecture and CI/CD integration. Being able to discuss your hands-on experience confidently will show them you’re the right fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially around data ingestion and pipeline stability. Think of examples where you’ve resolved schema drift issues or implemented monitoring systems. This will demonstrate your ownership mindset and ability to tackle complex infrastructure problems.
✨Understand Their Business Needs
Familiarise yourself with Fanvue’s mission and how data plays a crucial role in their growth. Be ready to explain how your work can directly support their goals, such as enabling advanced analytics and machine learning. This shows that you’re not just a techie but also understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about their current data infrastructure and future plans. Inquire about their approach to data governance and quality frameworks. This not only shows your interest in the role but also your proactive attitude towards ensuring data reliability and trust.