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Liberis Overview
🌱 Founded in 2007
💰 Over $3bn in funding to small businesses
🚀 CNBC & Statista Top 150 UK Fintechs for 2025
🌍 Global presence in 6 key locations
🧠 Community of over 290 innovative minds
👩🏾 🤝 👨🏼 Celebrating over 27 nationalities
🏢 Team experience from 740 companies
🎯 Named one of FinTech’s Finest 50 by Welcome to the Jungle
💪 Real Living Wage employer
Liberis is building an embedded finance platform for partners to offer innovative funding products to small business customers. We're a growth-stage fintech with teams in London, Nottingham, Atlanta, Stockholm, Munich, and Mumbai. Engineering is undergoing an AI-first transformation, rethinking team structures and delivery methods.
About our Data & Insights Team
We build data platforms and analytics to enable data-informed decisions and power AI and ML capabilities across the company. We're creating scalable data platforms that ingest partner transaction data and event streams, power analytics dashboards, and feed ML models with real-time features.
Team Functions
Data Platform Engineering
- Building and scaling ELT pipelines
- Managing data infrastructure on GCP
- Creating the foundation for analytics and ML feature stores
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Analytics Engineering
- Transforming raw data into trusted models using DBT and SQL
- Powering self-serve analytics and business intelligence for stakeholders
Data & Business Intelligence
- Building dashboards, partner-facing reports, and insights
- Driving business decisions and revenue outcomes
Role Responsibilities
- Design, build, and maintain resilient data pipelines
- Write Python code using DLT for declarative, testable, version-controlled pipelines
- Build and operate ML feature pipelines
- Own the operational health of systems you build
- Collaborate with analytics engineers to understand data needs and establish data quality standards
- Partner with the AI/ML platform team to design feature stores and model serving pipelines
- Identify and execute optimization work
- Mentor junior engineers
- Participate in technical decisions about platform direction
- Work cross-functionally with product teams, analytics engineers, BI specialists, and the ML platform team
Required Skills
- Proven experience in data engineering roles
- Hands-on experience building Modern Data Stack architectures
- Strong Python programming skills
- Fluent SQL
- Experience with cloud data platforms
- Experience with infrastructure-as-code tools
- Experience working in fast-moving environments
- Understanding of DevOps principles
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Bonus Points
- Experience with DLT or similar declarative ELT frameworks
- Experience with Google Cloud Platform ecosystem
- Experience with Kafka, Pub/Sub, or event streaming platforms
- Experience scaling data systems to 100M+ events/day
- Experience implementing data quality frameworks
- Background in fintech or high-stakes data reliability environments
- Experience working with distributed, asynchronous teams across timezones
- Experience in India tech ecosystem or building in resource-constrained environments
- Experience migrating from legacy data infrastructure to modern cloud-native stacks
Career Development
Liberis offers progression opportunities for both individual contributors and people managers. Check out our Engineering Career Framework for more information.
Hybrid Approach
Our hybrid working policy requires team members to be in the office at least 3 days a week. We value in-person collaboration and the importance of time spent together in the office.
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