Data Engineer-Data Platform & Analytics

Moody's offers a robust benefits package and a site-based role in Charlotte, NC. You will contribute to scalable data pipelines within Moody's Databricks ecosystem, supporting both enterprise and commercial data delivery. The team values reliability, observability, and responsible AI practices as part of a collaborative, growth-focused culture.

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• Parental leave
• Paid time off
• 401(k) retirement plan with employer contributions
• Life insurance
• Disability coverage
• Accident insurance
• Discounted employee stock purchase plan
• Tuition reimbursement

About the Team

This team sits at the core of Moody's Enterprise Data Platform (CORE), handling a highly complex and impactful portion of the data estate. It is a modern, innovation-driven data engineering group that powers Moody's extensive financial and corporate databases, enabling data-driven insights and supporting growth in an increasingly AI-enabled landscape.

Responsibilities

• Design, build, and run scalable ETL and ELT pipelines to support enterprise and commercial data delivery within Moody's Databricks environment.
• Develop and operate pipelines to ingest, transform, and publish data across domains.
• Create and optimize data transformations and validations using Python, PySpark, Scala, and SQL.
• Implement configuration-driven pipeline frameworks to onboard and manage datasets efficiently.
• Ensure data products are structured, performant, and ready for downstream consumption.
• Collaborate with stakeholders to define data contracts, schemas, SLAs, and quality standards.
• Apply best practices for data reliability, observability, and cost optimization.
• Contribute to CI/CD practices, including automated testing, deployment, and promotion.
• Support data governance initiatives, including data quality, lineage, and access controls.

Requirements

• Five or more years of experience in data engineering, building and operating production-grade data pipelines.
• Strong programming experience with Python, PySpark, Scala, and SQL.
• Proven experience designing or working with configuration- or metadata-driven data pipelines.
• Hands-on experience working within a Databricks-based data platform.
• Solid understanding of data modeling, schema evolution, and large-scale dataset management.
• Experience deploying and operating data solutions in AWS and Azure cloud environments.
• Working knowledge of CI/CD concepts and integrating data pipelines into automated workflows.
• Demonstrated proficiency in AI tools to streamline workflows, with awareness of responsible and ethical AI use.

Technologies

• Python
• PySpark
• Scala
• SQL
• Databricks
• AWS
• Azure