Skills and Competencies - 5-7 years of experience in data engineering, data warehousing, database administration, or a related discipline.
- Strong experience designing, building, and supporting ETL processes and scalable data pipelines.
- Proficiency in SQL and hands-on experience with relational databases and data warehouse technologies.
- Experience developing automation and data solutions using Python and/or JavaScript.
- Hands-on experience deploying and managing cloud-based solutions in AWS.
- Experience using Infrastructure as Code (IaC) tools such as Pulumi, CloudFormation, Terraform, or similar technologies.
- Strong understanding of data modeling, schema design, data quality, and data normalization best practices.
- Experience with Splunk, Cribl, observability platforms, security event data, or other large-scale operational data environments is a plus.
Education - Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field; equivalent combination of education and relevant experience will also be considered
- AWS certifications (e.g., AWS Certified Solutions Architect, Data Analytics Specialty, or similar) are a plus
- Relevant cloud, data engineering, or cybersecurity certifications are a plus
Responsibilities Build scalable data pipelines, ETL processes, and cloud infrastructure that power critical data platforms in a high-volume environment.
- Design, build, and maintain data pipelines that ingest, transform, and route security event data at scale
- Develop and support ETL processes that normalize and enrich data from a variety of source systems
- Build and maintain data warehouse and SQL datastore solutions that support cybersecurity, audit, and compliance programs
- Develop infrastructure as code (IaC) using tools such as Pulumi, CloudFormation, or AWS CDK to provision and manage cloud resources
- Create automation and tooling in Python and/or JavaScript to improve data quality, operational efficiency, and platform reliability
- Partner with cybersecurity, compliance, and engineering teams to understand data requirements and deliver reliable data solutions
- Monitor, troubleshoot, and optimize data pipeline performance, scalability, cost, and reliability
- Document data flows, schemas, operational processes, and technical implementations to support ongoing maintenance and audit readiness
About the Team Our Cybersecurity Data Management team is responsible for building, deploying, and operating the platforms and pipelines that collect, transform, route, and analyze security event data across Moody's environment. Our team enables cybersecurity detection and response, supports regulatory audit and compliance requirements, and delivers cybersecurity risk metrics that help protect the organization.
By joining our team, you will be part of exciting work at the intersection of data engineering, cloud technologies, and cybersecurity, leveraging AWS, Azure, and modern data platforms. As Moody's continues to advance its AI capabilities, our team plays a critical role in delivering the trusted, scalable, and high-quality data foundations that power analytics, automation, and AI-driven insights.
For US-based roles only: the anticipated hiring base salary range for this position is $116,500.00 - $169,000.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody's also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.
