Senior Data Engineer

DOU Polska; Warszawa; On-site; PLN 180,000 - 270,000; Full time

Job summary

DOU Polska in Warsaw is seeking a Senior Data Engineer to architect data-quality foundations for fraud-detection decision engines. You will embed directly into a product squad as a hands-on IC, delivering robust data pipelines and scalable infrastructure for AML and transaction-monitoring workloads.

Bring 5+ years of Python data engineering, hands-on Fraud/AML experience, and a track record of production-grade pipelines.

Qualifications

• 5+ years of Python for data engineering and production pipelines.
• Experience in Fraud, AML, or Transaction Monitoring systems.
• Proven ability to establish data-quality foundations for automated decisioning.

Responsibilities

• Architect and build robust data-quality frameworks powering decision engines.
• Design, scale, and maintain high-throughput production data pipelines.
• Build infrastructure and workflows for rapid deployment of fraud and transaction-monitoring rules.
• Bring deep domain knowledge in Fraud, AML, and Transaction Monitoring to production data engineering workflows.
• Share data engineering patterns and best practices across the organization.

Skills

Python

Data engineering

Fraud/ AML/ Transaction Monitoring

Data quality foundations

Production pipelines

Tools

Airflow

SQL

PostgreSQL

Google BigQuery

Job description

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).