Design, build, and manage a company's data platform, driving fraud prevention and security in digital payments. Strong expertise in data platforms, SQL, modern data modeling, and orchestration frameworks is required. Experience with sensitive financial data and regulatory environments is a plus.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
💻 Job Title: Senior Data Engineer
💰 Salary: ~£80-120k DOE (+80% of salary in equity!)
📍 Location: Central London, EC1 (3 office day/week)
🏦 Company: B2B FinTech / Fraud Prevention
👥 Employees: ~25
💸 Funding: $15m+ (Series A)
This London startup is building a new intelligence layer designed to bring more context and security to digital payments. Their technology analyses transactions in real time, gathering signals from multiple sources to determine whether a payment is legitimate or potentially fraudulent.
The platform combines distributed data systems, real-time investigations and AI-driven decisioning to help financial institutions detect scams while allowing legitimate payments to flow without unnecessary friction.
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Within 2 years of being founded, they're working with most Tier 1 banks and payment providers in the UK and are just getting started.
They're now looking for their first dedicated Data Engineer to design and build the foundations of their data platform - this is an opportunity to join at an early stage and shape how the company structures and scales its most valuable asset: data.
Key responsibilities:
- Designing and building the company’s core data platform and defining how data is modelled, stored, and accessed
- Bringing structure to a mixed data estate spanning warehouses, operational databases, event streams, and external data sources
- Building reliable and observable data pipelines that transform investigation data (structured and unstructured) into analytics and ML-ready datasets
- Ensuring data can be traced back to source evidence and investigation steps
- Implementing governance around sensitive financial data, including lineage, access control, and auditability
- Exploring graph or relationship-based representations of data to surface fraud patterns and connections
- Working closely with ML and product teams to ensure feedback loops — such as fraud outcomes and enrichment data — flow back into core systems
- Supporting experimentation with AI-driven investigation workflows by building reliable retrieval and data pipelines around unstructured information
- Writing production-grade software with a strong emphasis on reliability, security, and observability
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This role is less about maintaining pipelines and more about designing the foundations of a data platform that becomes a strategic product asset.
✅ Must have requirements:
- Strong programming skills, particularly in Python
- Experience designing data platforms in fast-moving environments and making architectural decisions while remaining hands-on (GCP / BigQuery experience highly preferred)
- Strong foundations in SQL and modern data modelling practices (dbt or similar frameworks)
- Experience building production data pipelines and working with orchestration frameworks such as Airflow, Dagster, Prefect or Temporal
- Infrastructure provisioning experience, ideally with Terraform
- Comfort working with messy, semi-structured or unstructured data sources
- Interest in building systems that support AI-driven or retrieval-based workflows
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👍 Bonus points for:
- Previous experience working in an early stage start-up, ideally FinTech
- Exposure to financial crime/fraud detection
- Experience working with sensitive or regulated data
🛂 VISA sponsorship is available if needed.
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