Senior Data Engineer (#5645)

N-iX; Union (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

N-iX is facilitating an engagement with a fast-growing European FinTech delivering corporate cards and related financial products to SMEs across the EU and UK in a regulated environment. The Senior Data Engineer will embed into a product squad as a hands-on IC, focusing on fraud detection, AML, and transaction monitoring data architectures.

The role emphasizes building robust data-quality foundations, scalable data pipelines, and rapid rule deployment workflows, leveraging modern tooling in

Qualifications

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

Responsibilities

• Architect and build data-quality frameworks to power decision engines.
• Design, scale, and maintain high-throughput production data pipelines.
• Build infrastructure and workflows for fast deployment of fraud rules.
• Share patterns and best practices across squads.

Skills

Python

Fraud domain knowledge

AML

Transaction monitoring

Data quality

Data pipelines

Production systems

Tools

Airflow

SQL

PostgreSQL

BigQuery

AWS

GCP

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).