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About Goldman Sachs
Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.
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Engineering- Dallas- Associate, Risk Governance – 10431267 is a role within the Engineering Division focused on managing risk and control self-assessment initiatives across the global enterprise. The associate will execute assessments for engineering processes including SDLC, CI/CD pipelines, cloud infrastructure, and production change management while identifying operational risks like infosec, cyber, and data loss. Key responsibilities include designing preventive controls such as automated policy-as-code, performing root-cause analysis on incidents with SRE leads, and translating technical risk into business language for senior management. The role requires proficiency in the NIST Cybersecurity Framework, Tableau for data visualization, and Generative AI tools like GitHub Copilot to automate evidence collection. Candidates must possess a relevant degree in fields such as Computer Science or Cyber Security and experience in data analysis, automated testing, and risk taxonomy management.
Execute division-wide Risk and Control Self-Assessment (RCSA) initiatives across engineering processes like SDLC, CI/CD pipelines, and cloud infrastructure.
Identify operational risks including technology operations, information security, cyber threats, third-party risks, and data loss.
Design and operationalize preventive and detective controls within engineering workflows such as automated policy-as-code and pipeline gates.
Utilize Generative AI tools to automate control evidence collection, draft policies, and summarize risk assessments.
Triage operational incidents and perform root-cause analysis with SRE and engineering leads.
Coordinate responses to internal audit findings and translate technical risks into business language for senior management.
Update the risk taxonomy and identify new controls to mitigate gaps in the Engineering Division's risk profile.
Perform data analysis, code reviews, and re-performance of logic to validate the remediation of system control weaknesses.
What we're looking for
Master’s degree in Computer Science, Information Systems, Management Science, Cyber Security, or a related field and one year of relevant experience.
Bachelor’s degree in Computer Science, Information Systems, Management Science, Cyber Security, or a related field and three years of relevant experience.
Experience with risk frameworks including the NIST Cybersecurity Framework (CSF).
Experience performing statistically driven analysis using various data analytical techniques to identify trends and propose process enhancements.
Experience visualizing complex data analyses from raw data in reports using tools such as Tableau.
Experience leveraging analytics and automation to enhance testing and sampling strategies for risk detection.
Experience developing processes and tools to identify and monitor data accuracy.
Ability to translate technical risk into business language for senior management forums.