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. 

• Must have 8+ years of professional Database Engineering experience, with a proven track record of leading technical projects and guiding senior engineers.
• Expert-level SQL skills including advanced T-SQL or PL/SQL, with strong production programming experience in Python OR Java OR Scala.
• Deep practical experience designing, tuning, and operating relational databases such as PostgreSQL and SQL Server alongside cloud data warehouses including Snowflake or Amazon Redshift and NoSQL Engines.
• Strong hands-on expertise with cloud data platforms on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including infrastructure provisioning using Terraform or CloudFormation.
• Proven ability to design and implement scalable data models using methodologies such as Star Schema or Data Vault in production environments.
• Experience building continuous integration and continuous delivery pipelines and implementing data quality, monitoring, and observability solutions.
• Experience building automated deployment pipelines and implementing data quality/observability monitoring tools.
• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency.

• Bachelor’s degree in Computer Science, Information Systems, or equivalent practical experience

• Lead the design of high-performance, scalable SQL and NoSQL data architectures, ensuring alignment with analytics, application, and data science platforms across the organization.
• Define and enforce enterprise-wide data modeling standards and best practices, reviewing schema designs across teams to drive scalability, consistency, and long-term maintainability while minimizing technical debt.
• Act as the technical escalation authority for complex database performance issues, driving deep optimization across query design, indexing strategies, partitioning, and server-level configurations.
• Own database reliability and performance at scale by proactively monitoring and optimizing resource utilization (CPU, memory, buffer pools) to ensure high availability and operational resilience.
• Architect end-to-end data integration frameworks, enabling seamless connectivity between internal and external systems across distributed platforms such as SQL Server, PostgreSQL, and Snowflake.
• Design and govern data synchronization, batching, caching, and consistency strategies to ensure reliable data flow across transactional and analytical ecosystems.
• Establish and implement robust data security and governance frameworks, including encryption (row/column-level), IAM roles, network controls, and adherence to regulatory standards such as GDPR and CCPA.
• Own the design and delivery of scalable, production-grade ETL/ELT pipelines, incorporating automated data validation, profiling, and observability mechanisms to ensure data quality and prevent downstream failures.
• Provide technical leadership and mentorship across engineering teams, conducting code and design reviews, guiding architecture decisions, and elevating engineering standards.
• Partner with Product Management and Data Science teams to translate complex business requirements into scalable technical architectures and actionable design artifacts, driving execution across multiple squads.

The engineering team builds advanced software, data platforms, and analytical solutions that power risk quantification for the global Property and Casualty insurance market. The team’s work enables organizations to better understand and manage exposure to natural and human-made catastrophes, including severe weather events, climate-related risks, cyber threats, and other complex systemic risks, by delivering scalable, secure, and high-impact data-driven solutions.

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.