Job Title: Data Engineer – DE20260503002
Date Posted: 03/05/2026
Job Code: DE20260503002
Key Responsibilities
Financial Crime Solution Development
- Design and implement Quantexa-based AML/KYC/Fraud solutions using entity resolution, rules, scoring, and graph analytics.
- Develop detection logic aligned with financial crime typologies (e.g., TBML, layering, structuring, mule networks, sanctions evasion).
- Translate AML and fraud risk requirements into technical specifications within the Quantexa platform.
Data Engineering & Modeling
- Build Spark-based ingestion pipelines for customer, account, transaction, and external intelligence data.
- Model entities and relationships for risk-based network views (customers → accounts → transactions → counterparties).
- Optimize data transformations and graph structures to support Quantexa’s Contextual Monitoring and investigations.
Quantexa Platform Configuration
- Configure and tune:
- Entity Resolution (ER) rules
- Scoring models
- Risk indicators and typologies
- Alerting logic for contextual monitoring
- Develop custom Scala/Java components to extend Quantexa functionalities when needed.
Integration & Deployment
- Deploy Quantexa pipelines into cloud or on-prem environments.
- Integrate Quantexa output with downstream systems: case management, alerting, dashboards.
- Support performance tuning, troubleshooting, and production maintenance.
Financial Crime SME Collaboration
- Work with AML investigators, FIU analysts, and compliance SMEs to validate typologies, false positives, and risk scoring.
- Present technical solutions in business terms to compliance and risk stakeholders.
Required Skills & Experience
Technical Skills
- Strong proficiency in Scala or Java, with hands-on Apache Spark experience.
- Experience with data engineering and Big Data ecosystems (Hadoop, Hive, HDFS, Parquet).
- Understanding of entity resolution, network analysis, and graph-based data models.
- SQL skills for data validation and data quality analysis.
- Experience integrating APIs, microservices, and ETL/ELT pipelines.
Financial Crime Domain Knowledge
- Familiarity with AML and fraud typologies such as:
- Transaction structuring / layering
- Trade-based money laundering
- Sanctions circumvention
- Watchlist matching
- Synthetic identities
- Account takeover / mule networks
- Understanding of the AML lifecycle: onboarding/KYC, CDD/EDD, TM alerting, case investigation, SAR reporting.
Tools & Platforms
- Experience with the Quantexa Decision Intelligence Platform (highly preferred).
- Experience with cloud platforms (Azure/AWS/GCP) and CI/CD tools (Jenkins, GitLab, Azure DevOps).
- Knowledge of Docker/Kubernetes is a plus.
Soft Skills
- Ability to translate financial crime risk requirements into technical solutions.
- Strong analytical, problem-solving, and debugging skills.
- Excellent communication and collaboration across engineering, analytics, and compliance teams.
- Ability to work in agile delivery environments.
Nice-to-Have
- Knowledge of graph databases (Neo4j, TigerGraph).
- Prior work with AML transaction monitoring systems (Actimize, SAS AML, Oracle FCCM).
- Experience with ML-based risk scoring or anomaly detection.
- Certifications such as CAMS, ICA, or cloud certifications (Azure/AWS).
Apply Now
Salary: $ 94,266 / year
Location: East Brunswick, NJ
