Python Data Engineer - W2 - Need NJ Locals

Position: Mid-Level Python Data Engineer

Locations: Iselin, NJ (Only Locals, 3 days a week in any location)

Contract: 2-year contract

Interview process: one and done video interview

Must have: 7+ years of Python Development, SQL, and data manipulation libraries (e.g., Pandas, NumPy), strong understanding of data governance, model validation, and regulatory compliance, and Oracle Database Experience.

**Huge NICE TO HAVE Transaction monitoring/AML domain knowledge**

Role Description:

We are seeking a skilled Python Data Engineer with a strong background in Anti-Money Laundering (AML) and transaction monitoring systems. The ideal candidate will be responsible for designing and maintaining robust data pipelines, supporting AML analytics, and enhancing the efficiency of financial crime detection systems.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL processes using Python and SQL.
• Collaborate with AML and Financial Crimes teams to improve detection models and reduce false positives.
• Develop tools and scripts to support alert optimization, scenario tuning, and threshold calibration.
• Perform data profiling, cleansing, and validation on large volumes of transactional data.
• Integrate data from various sources, including core banking systems, case management tools, and AML platforms.
• Conduct statistical analysis to evaluate model performance and support regulatory reporting.
• Ensure compliance with BSA/AML regulations and internal governance standards.
• Document data workflows, methodologies, and results in an audit-ready format.

Required Qualifications:

• Bachelor s or Master s degree in Computer Science, Data Science, or a related field.
• Proficiency in Python, SQL, and data manipulation libraries (e.g., Pandas, NumPy).
• 7+ years of Python Engineering /Python Data Developer
• 3+ years of experience in data engineering or analytics, preferably in a financial crime or AML context.
• Experience with AML data, such as transaction monitoring alerts, customer risk scoring, and KYC data.
• Familiarity with AML systems (e.g., Actimize, SAS AML, Oracle FCCM).
• Strong understanding of data governance, model validation, and regulatory compliance.

Preferred Skills:

• Experience with cloud platforms (AWS, Google Cloud Platform, or Azure).
• Knowledge of workflow orchestration tools (e.g., Airflow).
• Exposure to big data technologies (e.g., Hadoop, Spark).
• Understanding of machine learning concepts for anomaly detection.