Founding Data Engineer

💻 Job Title: Founding Data Engineer

💰 Salary: up to ~£120k (+ very generous equity ~£100k)

📍 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. 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 with strong Software Engineering background and Data Platform Engineering expertise. In this role, you'll 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:

• Exploring graph or relationship-based representations of data to surface fraud patterns and connections
• 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
• 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

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• Writing production-grade software with a strong emphasis on reliability, security, and observability

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:

• Greenfield 0 > 1 experience, designing and building data platforms from the ground up
• Cloud native data platform experience (GCP / BigQuery preferred)
• Strong expertise in SQL and dbt + experience modelling data for both analytics and downstream ML consumption
• Exposure to graph databases, knowledge-graph systems or entity-resolution problems (e.g. Neo4j, Google Knowledge Graph, GraphRAG etc.)
• Strong opinions, weakly held - engineering excellence with low ego and ability to collaborate well in a small cross-functional team

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• Software Engineering background / strong programming skills, particularly in Python
• 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

👍 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

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