At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and Competencies
- 3-5 years of experience in data engineering, data warehousing, database administration, or a closely related discipline
- Experience building and operating ETL and data pipeline architectures
- Hands-on experience with SQL and relational/database warehouse technologies
- Proficiency in Python and/or JavaScript for pipeline development, automation, and tooling
- Experience deploying and managing infrastructure in AWS cloud environments
- Experience with Infrastructure as Code tools such as Pulumi, CloudFormation, CDK, or similar technologies
- Strong understanding of data modeling, schema design, and data normalization principles
- Strong troubleshooting, analytical, and problem-solving skills with experience operating production data systems at scale
- Experience with Splunk (Splunk Cloud, SPL) and/or Cribl (Cribl Stream, Cribl Cloud) preferred
- Familiarity with security event data, cybersecurity data platforms, or cybersecurity-adjacent data engineering environments preferred
- Experience with CI/CD pipelines for data infrastructure deployment preferred
- Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency; interest in exploring AI systems and willingness to develop awareness of responsible AI practices, including risk management and ethical use
Education
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Cybersecurity, or a related technical field required
- AWS certifications (e.g., Solutions Architect, Data Analytics Specialty) or other relevant cloud certifications preferred
Responsibilities
The Cybersecurity Engineer, Data Engineering will design, build, and operate the data pipelines, cloud infrastructure, and automation capabilities that support cybersecurity data platforms, enabling the reliable collection, transformation, and delivery of security data across Moody’s environment.
- Design, build, and maintain data pipelines that ingest, transform, and route security event data at scale through platforms such as Cribl Cloud, Splunk Cloud, and custom-developed tooling
- Operate and optimize SQL datastore capabilities supporting cybersecurity detection, audit, compliance, and reporting use cases
- Develop and maintain ETL processes to normalize, enrich, and deliver data from a wide variety of source systems
- Write and maintain Infrastructure as Code to provision, manage, and automate AWS resources supporting cybersecurity data platforms
- Build automation and engineering solutions in Python and/or JavaScript to support data quality, pipeline development, and operational efficiency
- Collaborate closely with detection engineering, threat hunting, compliance, and cybersecurity stakeholders to understand data requirements and ensure high-quality data delivery
- Monitor, troubleshoot, and continuously improve pipeline performance, reliability, scalability, and cost efficiency
- Document data flows, schemas, architecture, and operational procedures to support audit, compliance, and operational requirements
- Contribute to continuous improvement initiatives, automation strategies, and platform enhancements that reduce manual effort and increase resiliency
About the Team
The Cybersecurity Data Management team builds, deploys, and operates the platforms and pipelines that collect, transform, route, and analyze event data across Moody’s environment. The team directly supports cybersecurity detection and response, regulatory audit and compliance, and cybersecurity risk management programs. Operating at scale across AWS and Azure, the team develops custom tooling in Python and JavaScript and supports critical platforms including Cribl Cloud, Splunk Cloud, and Microsoft Fabric. This collaborative environment partners closely with cybersecurity, compliance, and engineering teams to deliver secure, scalable, and reliable data solutions that enable informed decision-making and effective security operations.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.