Data Engineer, Technology Risk

The Technology Risk Data Engineer role on the Enterprise Risk team focuses on developing and operating technology risk registers and automating risk analysis and reporting. The position partners across technology, operations, and compliance teams to evaluate emerging risks and deliver clear insights to senior leadership.

Technology Risk Data Engineering Responsibilities

• Design, implement, and maintain structured technology risk registers.
• Support alignment with 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 identify mitigation strategies.
• Build and maintain infrastructure that enables automated risk analysis and reporting.
• Develop scripts and tools to streamline data collection, processing, and visualization, using technologies including Python, AI agents, LLMs, SQL, C++, and Shell Scripting.
• Define, track, and report key performance indicators (KPIs) and risk indicators.
• 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 address risk-related problems.
• Stay current with industry trends and emerging tools to improve risk analytics capabilities.

Required Qualifications

• 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.
• Mater’s Degree in Data Analytics is a plus.
• Strong understanding of technology risk domains, including cybersecurity, cloud, and data privacy.
• Experience in DevOps with responsibility for infrastructure components supporting production, POC, and UAT environments.
• Proficiency in Python, including experience with data automation and analytics.
• Ability to write and review code across multiple programming languages.
• Familiarity with AI/ML tools and LLMs in the context of risk analysis.
• Experience setting up cloud platform infrastructure in AWS, Azure, or GCP.
• Experience with data visualization tools, such as Power BI and Tableau.
• Experience with GitHub automated code deployments.
• Experience working with CI/CD pipelines to automate workflows that build, test, and deliver software updates.
• Excellent interpersonal and communication skills, with the ability to work cross-functionally.
• Strong analytical and problem-solving abilities.

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 audit and risk management is a plus.

Location and Experience Level

Atlanta, GA (onsite). Minimum experience: 2 years.