Let's begin! Senior Data Engineer- Cybersecurity

Moody's•Golden, CO

4d•Hybrid

About The Position

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. 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.

Requirements

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.

Nice To Haves

Experience with Splunk, Cribl, observability platforms, security event data, or other large-scale operational data environments is a plus.
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