Data Pipeline Engineer (Fraud Detection)

Core Responsibilities:

Design, build, and maintain data pipelines for fraud detection.

Develop and optimize SQL-based data transformations for large-scale datasets.

Ensure data quality, consistency, and integrity across antifraud systems and datasets.

Build and maintain feature tables for fraud rules and scoring models.

Work with streaming and event-based data (e.g., transactions, logins, device signals).

Optimize query performance and data models for high-volume data (millions+ records).

Develop, implement, and maintain fraud detection rules (SQL / rule engines).

Analyze fraud patterns (ATO, card fraud, onboarding fraud, etc.) and translate them into data-driven controls.

Monitor rule performance (false positives / false negatives) and continuously improve detection logic.

Perform deep-dive analysis of fraud cases and emerging patterns.

Requirements:

• Strong SQL expertise required.

• Attention to detail and data accuracy.

• Ability to communicate findings to both technical and non-technical stakeholders.

• Ownership mindset and proactive approach.