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M
Moody's
Senior Data Engineer- Cybersecurity
Career Insights for Cyber Security Engineer
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Based on Colorado data
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What they do
A Cyber Security Engineer designs systems that protect the security of large databases, including databases with customer information and patient files. Examines client computer systems, identifies weak points in security, develops and implements new systems, monitors and responds to security issues.
$108,646 / year median in Colorado
+4% projected growth
Job Description
Senior Data Engineer- Cybersecurity Moody's - 3.6 Golden, CO Job Details Full-time $116,500 - $169,000 a year 6 hours ago Benefits Employee stock purchase plan Health insurance Dental insurance 401(k) Tuition reimbursement Paid time off Parental leave Vision insurance Employee discount Qualifications Data integrity assurance Data model design Data quality checks Commercial use (data warehousing systems) Data Integration (Data management) Bachelor's degree in information technology Computer Science Data modeling projects Tooling 5 years Infrastructure as Code (IaC) AWS Certification Process design Scalable systems Improving operational efficiency Schema design AWS Certified Data Analytics - Specialty SQL Data integrity and documentation ETL process automation Bachelor's degree in engineering Data integrity process (data warehousing) JavaScript Terraform Splunk Security Event Management (security operations) Log analysis tools Scalability Cloud automation Cloud solution engineering Full Job Description 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 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.