Senior Data Engineer

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).