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).