ABOUT OUR COMPANY:

LemFi (YC S21, Series B) is revolutionizing cross-border financial services for immigrants through its multi-currency platform, processing over $1 billion in monthly transactions. We provide instant remittances, foreign exchange services, and multi-currency accounts, all in one seamless experience.
With 300+ employees across 15+ countries, our platform supports twelve currencies and integrates directly with local banks and mobile money providers, ensuring fast, low-cost transactions. But we’re not stopping at payments. LemFi is building a comprehensive financial ecosystem empowering immigrants with the financial tools they need to thrive—wherever they go.
Our vision: To build the first full-stack financial services hub for the world’s immigrant population.

JOB SUMMARY:

We are looking for a Credit Data Engineer to join our team and help build, scale, and optimise the data infrastructure at the core of our lending business.
This is a hands-on engineering role, ideal for someone who thrives on building and maintaining robust data pipelines that power underwriting, credit decisioning, and portfolio analytics. You’ll work closely with credit risk, product, and data science teams to deliver the data foundations that enable innovative credit products and actionable insights.
Your work will directly influence our ability to automate decisions, monitor performance, manage risk, and deliver a best-in-class lending experience. You will join our growing Data team, with your focus dedicated to work with the Credit business unit.

Key Responsibilities:

• Design, build, and maintain data pipelines that support credit risk modelling, underwriting, portfolio management, and regulatory reporting.
• Connect and ingest data from core ledger systems, transaction processors, credit bureaus, open banking APIs, and third-party providers.
• Implement and maintain robust processes to ensure data accuracy, completeness, and reliability. Implement automated checks, anomaly detection, and data validation routines.
• Deliver production-ready datasets that power credit decision engines, risk models, and affordability assessments in real time.
• Work closely with credit risk, analytics, data science, product, and compliance teams to understand requirements and deliver fit-for-purpose data solutions.
• Monitor data infrastructure, optimise for scalability and performance, and troubleshoot issues as they arise.
• Maintain clear documentation of data flows, pipelines, and business logic. Support data governance and access controls in line with regulatory requirements.

REQUIREMENTS:

• 1–3 years’ experience as a Data Engineer, or similar role, preferably within UK consumer lending, fintech, or financial services
• Hands-on experience with building data pipelines, use of SQL, Python, and relevant data engineering tools (e.g.,Snowflake, dbt, third-party ingestion tools, Dagster).
• Comfortable working with transactional data, credit bureau data, and open banking APIs.
• Understand the importance of and implement solutions for data quality, lineage, and security in a regulated environment.
• Enjoy collaborating with cross-functional teams and turning messy real-world data into clean, reliable, production-ready datasets.
• Excited to work in a fast-paced, highly driven environment.

• Design, build, and maintain data pipelines that support credit risk modelling, underwriting, portfolio management, and regulatory reporting.
• Connect and ingest data from core ledger systems, transaction processors, credit bureaus, open banking APIs, and third-party providers.
• Implement and maintain robust processes to ensure data accuracy, completeness, and reliability. Implement automated checks, anomaly detection, and data validation routines.
• Deliver production-ready datasets that power credit decision engines, risk models, and affordability assessments in real time.
• Work closely with credit risk, analytics, data science, product, and compliance teams to understand requirements and deliver fit-for-purpose data solutions.
• Monitor data infrastructure, optimise for scalability and performance, and troubleshoot issues as they arise.
• Maintain clear documentation of data flows, pipelines, and business logic. Support data governance and access controls in line with regulatory requirements