Compunnel Inc.

Compunnel Inc.

Data Engineer

Smithfield, Rhode Island, USA · Contract

Sponsorship not specifiedDetected 56 days ago
SQLNoSQLMongoDBData EngineeringResearchCommunicationProblem SolvingPublic Speaking

About the role

  • We are seeking a Senior Data Engineer Fraud Analytics to design, build, and maintain data solutions that support the research, detection, and analysis of fraud events.
  • This role partners closely with fraud analysts, investigators, and business stakeholders to transform large, complex datasets into actionable insights that reduce fraud risk and improve detection strategies.

Responsibilities

  • Desi gn, develop, and optimize data pipelines to support fraud research and analytics use cases.
  • Work extensively with Oracle databases to support enterprise-scale fraud analytics.
  • Investigate data anomalies, identify fraud patterns, and support root-cause analysis.
  • Partner with fraud operations, compliance, and analytics teams to translate business questions into technical data solutions.
  • Document data models, logic, and findings clearly for both technical and non-technical audiences.
  • Support continuous improvement of fraud detection and monitoring processes through data-driven insigh ts.

Requirements

  • Advanced proficiency in SQL (complex joins, subqueries, performance tuning, data validation).
  • Strong hands-on experience with Oracle databases.
  • Working knowledge of MongoDB or similar NoSQL technologies.
  • Ability to work independently while collaborating across cross-f unctional teams.
  • Bachelors Degree

Nice to have

  • Exp erience supporting fraud, risk, compliance, or financial crime analytics.
  • Exposure to scripting or data-processing languages such as Python.
  • Experience working in regulated or financial services environments.
  • Certifications Rel evant certifications in data engineering, databases, or analytic s preferred.
  • Research and analyze fraud events by querying and correlating structured and unstructured data across multiple platforms.
  • Write complex, high-performance SQL queries to extract, transform, and analyze large datasets.
  • Utilize MongoDB for handling semi-structured and unstructured fraud-related data.
  • Ensure data accuracy, consistency, and reliability across fraud datasets.
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