Data Engineer II

• Design, build, and optimize data pipelines to ingest, process, and prepare data for use in insider risk detection models
• Join, filter, and integrate diverse data sources to create comprehensive datasets that enable effective and accurate insider risk detections
• Work with large datasets, applying advanced data transformation techniques to ensure data quality and accessibility for risk detection
• Develop, test, and deploy insider risk detection models based on data-driven insights to proactively identify anomalous or risky behavior patterns
• Collaborate with insider risk team members to define and refine detection use cases, ensuring they are accurate, scalable, and aligned with business needs
• Share knowledge and actively contribute ideas in team technical discussions
• Maintain and monitor insider risk engineering systems to ensure reliable operation, security, and compliance with internal engineering standards and policies
• Join on-call rotations, lead incident response, and drive thorough root-cause analysis
• Document data processes, detection workflows, and system configurations to support future development and maintenance
• Use development and coding best practices (e.g., reusable, modular)
• Own end-to-end quality for the code you deliver, including testing and DevOps automation

• Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) experience in business analytics, data science, software development, data modeling, or data engineering
• OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years experience in business analytics, data science, software development, data modeling, or data engineering
• OR equivalent experience
• Candidates must be able to meet Microsoft, customer and/or government security screening requirements
• Microsoft Cloud Background Check
• Citizenship & Citizenship Verification

• 4+ years of experience in data engineering, data science, or a hybrid data engineering/data science role
• Proficiency in query languages (e.g., SQL, KQL)
• Experience with object-oriented programming languages (e.g., Python, C#, Java, or C++)
• Experience with security product usage such as Insider Risk Management or Sentinel
• Demonstrated ability to build and manage data systems in the cloud
• Experience with big data systems and tools, such as PySpark, Databricks, or Azure Synapse
• Familiar with data engineering best practices like layered data architecture, data modeling, and developing reliable and scalable data pipelines
• Strong understanding of engineering and security compliance standards, with experience in regulated environments
• Excellent problem-solving skills and attention to detail
• Experienced working within agile frameworks such as Scrum and Kanban

Benefits and other compensation