Senior Data Engineer - Cloud Data Ops for Cybersecurity

PassFort; Golden (CO); On-site; USD 117,000 - 169,000; Full time

Job summary

Moody's is seeking a data engineering professional to design, build, and scale data pipelines and cloud infrastructure in a Cybersecurity Data Management context. You will ingest, transform, and route security event data, while ensuring data quality and compliance across high-volume environments.

Qualifications include 5–7 years in data engineering or related fields, strong SQL, AWS experience, and IaC tooling (Pulumi/CloudFormation/Terraform).

Qualifications

• 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.

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.

Skills

Data engineering

Data warehousing

ETL design

SQL

Python

JavaScript

AWS

IaC

Data modeling

Observability tooling

Education

Bachelor's degree in Computer Science / IT / Engineering / Data Science

AWS certifications

Cloud / cybersecurity certifications

Tools

Pulumi

CloudFormation

Terraform

AWS CDK

Splunk

Cribl

Job description

Moody's is seeking a data engineering professional to design, build, and scale data pipelines and cloud infrastructure in a Cybersecurity Data Management context. You will ingest, transform, and route security event data, while ensuring data quality and compliance across high-volume environments.

Qualifications include 5–7 years in data engineering or related fields, strong SQL, AWS experience, and IaC tooling (Pulumi/CloudFormation/Terraform).