Senior Data Engineer
Summary
This Senior Data Engineer role involves building data-quality frameworks and high-throughput pipelines for fraud detection and AML systems within a European fintech company. The position requires deep domain expertise in transaction monitoring and strong Python skills to support automated decision engines.
We are looking for a Senior Data Engineer with specialized domain expertise in fraud detection, Anti-Money Laundering (AML), or transaction-monitoring systems to establish data-quality foundations for decision engines. Our client is a fast-growing European FinTech company in the Business Spend Management space — providing corporate cards and related financial products to SME and mid-sized businesses across the EU and UK in a regulated environment. You will embed directly into a product squad as a hands-on Individual Contributor (IC).
Key Responsibilities
- Architect and build robust data-quality frameworks specifically designed to power decision engines.
- Design, scale, and maintain reliable, high-throughput production data pipelines.
- Build infrastructure and workflows that enable fast, seamless deployment of fraud and transaction-monitoring rules.
- Bring deep domain knowledge in Fraud, AML, and Transaction Monitoring to production data engineering workflows.
- Multiply the output and quality of your squad while sharing data engineering patterns and best practices across the organization.
Requirements
- Strong, senior-level 5+ years expertise in Python for data engineering and production pipeline development.
- Experience/background in Fraud, AML, or Transaction-Monitoring systems.
- Proven track record of establishing data-quality foundations for automated decisioning systems.
- Extensive experience building production data pipelines and supporting rapid rule deployment workflows.
Nice-to-Have Skills
- Hands-on experience with Airflow, SQL, PostgreSQL, and Google BigQuery (standard stack for data/analytics workloads).
- Experience working in hybrid cloud environments (AWS primary + GCP analytics).
- Familiarity with modern engineering workflows (Linear, GitHub, Notion, Slack) and AI-assisted development (Claude Code, GitHub Copilot).