Data Engineer

About this role

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.


Employment eligibility to work in the U.S. is required, as Moody’s will not pursue visa sponsorship for this position


Skills and Competencies

• 1–3 years of experience in data engineering, backend engineering, or a related technical role.
• Foundational experience working with the Databricks Lakehouse (Delta Lake) or a comparable platform (Snowflake, BigQuery); exposure to Delta Live Tables (DLT) is a plus.
• Familiarity with orchestration tools such as AWS MWAA (Managed Workflows for Apache Airflow) or Databricks Workflows.
• Solid SQL skills and working knowledge of Python; exposure to Spark and dbt is preferred.
• Understanding of DataOps principles: CI/CD for data pipelines, automated testing, and environment promotion practices.
• Awareness of data security fundamentals—encryption at rest and in transit, role-based access control, secrets management—and a willingness to deepen that knowledge.
• Understanding of data observability a...