Principal Data Engineer
Funding Circle is hiring a Principal Data Engineer in London, United Kingdom. Level rates it ; you can apply on Funding Circle.
Level's read on this job
- Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
- Some of the work can be done remotely, according to the posting.
- The posting mentions Snowflake, AWS and data architecture among its tools and skills.
- Level classes it as a lead role.
- Funding Circle has 21 other open roles on Level.
AI in this role
Lead the data engineering and platform architecture strategy, focusing on modern cloud data stack migrations.
We’re on a mission to back the UK’s small businesses like no one else 🚀
Small businesses are the backbone of the economy, and we’re here to help them win. We’ve built a platform that uses clever data to get them the funding they need in minutes, not weeks.
At Funding Circle, we have the restless energy of a fintech start-up with the stability of a public company. It’s a unique mix that gives Circlers the autonomy to take ownership and the scale to make an impact that truly counts.
We’re a high-performing team that chooses to lift each other up. We challenge, we champion, and we have each other’s backs - because we know that when we stand together, we move faster and build better.
The impact is real: Last year alone, the businesses on our platform generated £7.2bn for the UK economy 📈 Come and join a mission that matters!
[Read our Impact Report] | [See our Trustpilot]
The role ⚡
📍 London (Hybrid) | 🤝 2 days in the office | 💰 Competitive Salary + Benefits
As Principal Data Engineer you are the primary technical authority for Funding Circle's Data Engineering and Data Platform architecture, designing innovative solutions on Snowflake and AWS. Reporting to the VP of Data and sitting on the Data Leadership Team, you lead the analysis, architecture, design and development of our Data and Analytics estate.
You own the Data Platform strategy and the multi-phased roadmap to our Future State Data Platform, and you are the key technical team member advising on the migration to the Future State Data Platform.
Own the Data Platform strategy and execute the multi-phased roadmap for migrating to the Future State Data Platform on Snowflake and AWS, advising on migration architecture, transition states, historical data migration and legacy decommissioning.
Lead the architecture, design and development of scalable cloud data warehouse, lakehouse, streaming and analytics solutions.
Define ingestion, transformation and orchestration patterns, naming and structural conventions, and the publication boundary between Product Engineering and Data Engineering.
Identify, mitigate and resolve architectural bottlenecks, control weaknesses and technical debt across the data ecosystem.
Own the Data as a Product Community of Practice and the standards that bind every Data Product: metadata and data contract specifications, output port and schema design, data product versioning, DQ requirements, SLA and SLO declarations, and semantic layer conventions
Champion data quality, lineage, observability and governance, ensuring checks, SLAs and alerting are expressed as code and monitored in production rather than asserted on a page.
As a key member of the Data Architecture Review Board, work on and carry formal decision rights over data architecture decisions, ensuring every proposal is engineering-viable, consistent with the platform direction and properly recorded.
What we’re looking for 🌱
We value deep expertise, but a growth mindset and good energy are what really make our team click. We’re a group that chooses to lift each other up and think smart every day.
A minimum of 10 years of experience in Data & Analytics, with experience in Staff, Principal (or equivalent) roles in Data Engineering, Data Architecture, or Data Platform, ideally within digital products or FinTech.
Extensive hands-on experience designing, building and operating cloud data platforms on Snowflake and AWS, and a proven track record leading complex, large-scale migrations from legacy systems.
Experience designing data products across source-aligned, aggregate and consumer-aligned patterns.
Proven ability to architect and scale modern cloud data platforms using Snowflake, Apache Iceberg, Amazon Redshift, and S3.
Hands-on expertise in developing robust data transformation pipelines and orchestrating complex workflows using dbt and Apache Airflow.
Strong track record of automating infrastructure and deployment pipelines using Infrastructure as Code tools like Terraform and GitHub Actions.
Ability to implement data governance, technical catalogues, end-to-end lineage, and data product portals to maximise data observability.
Experience leveraging AI tooling to accelerate data engineering workflows, migrations, and platform readiness for AI applications.
Experience establishing or leading a community of practice, driving standards adoption across teams.
Proven track record of cross-functional partnership with Product, Engineering, Data Science, and Governance teams.
Act as a technical bridge and mentor, training "builders" across the company to move from basic AI usage to sophisticated system creation.
Able to architect custom AI solutions and smart automated systems that are safe, maintainable, and aligned with our long-term mission
Act as a technical bridge and mentor, training “builders" across the company to move from basic AI usage to sophisticated system creation
We’re building a place where everyone truly feels they belong. Even if your past experience doesn't align perfectly with every requirement, we'd still love to hear from you.
Why join us? 💜
We back you to build an incredible career and by joining us, you'll be part of one of The Sunday Times Best Companies to Work For 2026! As a flexible-first employer, we use a "best of both" approach. We’ll see you in our London office to collaborate – with barista coffee and subsidised Just Eat lunches on us!
Our Circler Proposition focuses on five areas:
Flexibility: We provide a benefit allowance you can tailor to your own life and family.
Health: This includes private medical and dental, health assessments, and access to a digital GP.
Wealth: We offer life assurance, share schemes, and financial coaching.
Development: You get a dedicated annual learning allowance to help you level up.
Lifestyle: We have electric car and cycle-to-work schemes, plus season ticket loans.
We also have award-winning parental leave policies. We're here to support you through the big life moments, from fertility treatments to new additions to the family.
Ready to join a mission that matters? We’d love to chat!
How we rate this
Principal Data Engineer at Funding Circle rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data architecture was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Walk me through how you've used Snowflake in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Architecture, Data Engineering, Data Modeling, ETL, and Snowflake. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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