JOB DESCRIPTION Insight Global is looking for a highly technical Splunk Consultant to join the Fraud Services team at one of our largest banking clients on a 6-month contract. This role is centered on maximizing the value of Splunk data to uncover fraud patterns, identify vulnerabilities, and improve detection capabilities.

The successful candidate will be responsible for the following:

• Serve as the Splunk SME, designing and optimizing advanced queries, dashboards, and alerting frameworks.
• Analyze log data, indexes, and metadata to uncover fraud patterns, anomalies, and root causes.
• Improve data quality and structure, including deduplication and standardization of large-scale datasets.
• Translate complex data into actionable fraud and cyber risk insights for business stakeholders.
• Integrate Splunk with multiple data sources (e.g., SQL databases, Databricks, APIs, Excel) to create a unified view of activity.
• Build and enhance automation workflows (alerting, tuning, noise reduction) to improve detection efficiency.
• Support fraud investigations and risk quantification by leveraging Splunk-driven intelligence.
• Identify vulnerabilities and control gaps and partner with IT to strengthen detection and monitoring capabilities.

We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position. REQUIRED SKILLS AND EXPERIENCE

• Expert-level Splunk expertise: Advanced SPL querying, dashboarding, alerting, and metadata/index analysis.
• Strong understanding of Splunk architecture and data ingestion pipelines, including parsing, normalization, and log data structures.
• Proven ability to analyze large, complex datasets to identify anomalies, patterns, and risks.
• Demonstrated critical thinking and problem-solving skills in data-driven environments.
• Hands-on experience with SQL (MySQL, PostgreSQL) and integrating multiple data sources (e.g., APIs, Excel, Databricks). NICE TO HAVE SKILLS AND EXPERIENCE
• Experience in fraud analytics, cybersecurity, or risk management environments.
• Exposure to high-volume log or customer activity data environments.
• Familiarity with Python or similar scripting languages for data manipulation and automation.
• Experience working in financial services or other regulated industries.