Data Engineer, Technology Risk

Work on the Enterprise Risk team as a Technology Risk Data Engineer, building automated technology risk registers and analysis to inform senior leadership.

Responsibilities

• Design, implement, and maintain structured technology risk registers.
• Maintain alignment between technology risk registers and enterprise risk frameworks and regulatory expectations.
• Monitor and evaluate emerging technology risks, including AI, cloud, third-party, and cybersecurity.
• Collaborate with stakeholders to assess impact and mitigation strategies.
• Build and maintain infrastructure to support automated risk analysis and reporting.
• Develop scripts and tools to streamline data collection, processing, and visualization, using Python, AI agents, LLMs, SQL, C++, and Shell Scripting.
• Define, track, and report key performance indicators (KPIs) and key risk indicators (KRIs).
• Create dashboards and visualizations to communicate risk insights to senior leadership.
• Partner with internal clients across technology, operations, and compliance teams.
• Translate complex technical risk concepts into actionable business insights.
• Use modern technologies, including Python, AI agents, and large language models (LLMs), to solve risk-related problems.
• Stay current with industry trends and emerging tools to enhance risk analytics capabilities.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• 2+ years of experience in technology risk, data engineering, IT Audits, DA Audits, or related roles.
• Strong understanding of technology risk domains (e.g., cybersecurity, cloud, data privacy).
• Experience in DevOps with responsibility for infrastructure components for production, POC, and UAT environments.
• Proficiency in Python and experience with data automation and analytics.
• Ability to write and review code in multiple coding languages.
• Familiarity with AI/ML tools and LLMs and how they apply to risk analysis.
• Proven experience setting up cloud platform infrastructure using AWS, Azure, or GCP.
• Experience with data visualization tools, including Power BI and/or Tableau.
• Experience with GitHub automated code deployments.
• Experience with CI/CD pipelines to automate workflows that build, test, and deliver software updates.
• Excellent interpersonal and communication skills with ability to work cross-functionally.
• Strong analytical and problem-solving abilities.
• Master’s degree in Data Analytics is a plus.

Technologies

• Python
• AI agents
• LLMs
• SQL
• C++
• Shell Scripting
• Power BI
• Tableau
• GitHub
• CI/CD pipeline
• AWS
• Azure
• GCP
• AI/ML tools

Preferred knowledge and experience

• Experience in financial services or market data environments.
• Knowledge of regulatory frameworks, including NIST, ISO 27001, and FFIEC.
• Experience with risk management platforms or GRC tools.
• Experience in risk-related fields such as Audit and Risk Management is a plus.

Location: Atlanta, GA (onsite)

Minimum experience: 2 years