MW Partners is currently seeking a Fraud Data Engineer to work for our client who is a global leader in multimedia and creativity software products.

Responsibilities and duties:

• Design, build, and maintain robust ETL/ELT pipelines (batch and streaming) for structured and unstructured data using SQL and Python/PySpark.
• Collaborate with data scientists and business stakeholders to model, query, and visualize complex entity relationships using Neo4j.
• Optimize Neo4j data models and Cypher queries for scalability and performance.
• Build and manage large-scale ML feature stores and integrate them with AI and agentic workflows.
• Develop and maintain integrations across AWS (S3) and Azure (Blob Storage, VMs) , and third-party threat intelligence APIs to enrich fraud detection and investigation workflows.
• Automate workflows using Apache Airflow or equivalent orchestration tools.
• Apply DataOps best practices, including version control (Git), CI/CD, and monitoring for reliability and maintainability.
• Implement and enforce data quality, lineage, and governance standards across all data assets.

Requirements:

• Master's degree in Statistics, Mathematics, Computer Science, or a related field (or bachelor's degree with equivalent experience)
• 8+ years of experience in data engineering or a related field.
• Proven success in ETL/ELT design and implementation, including batch and streaming pipelines.
• Strong proficiency in SQL, Python, and PySpark.
• Hands-on experience with Neo4j (data modeling, Cypher, query optimization).
• Experience building ML feature stores and integrating with AI/ML pipelines.
• Working knowledge of AWS and Azure data services.
• Familiarity with Apache Airflow or similar orchestration tools.
• Proficient in Git and CI/CD workflows.
• Strong understanding of data quality, lineage, and governance
• Nice to Have: Experience with Databricks.

For a confidential discussion or to find out more, contact Amit Kumar on 909-206-4330 or apply now.