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# Data Engineer-Data Platform & Analytics

- **Company:** Moody's Corporation
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $95,500.0 - $138,550.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Computer Programming, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Python (Programming Language), Metadata, Standard Sql, Scala (Programming Language), Enterprise Data Management, Pyspark, Information Technology, Data Pipelines, Databricks
- **Published:** August 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=5b950c881dbe97c6

## About the Role

* 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, * Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

## Description

This role is responsible for designing, implementing, and operating scalable ETL and ELT pipelines to support enterprise and commercial data delivery within Moody's Databricks ecosystem.

 * Develop and operate scalable ETL and ELT pipelines to ingest, transform, and publish data across domains
 * Build 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 optimized for downstream consumption
 * Partner 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

About the Team
This team plays a mission-critical role within the Enterprise Data Platform (CORE), supporting a highly complex and impactful component of Moody's data estate. The group is a modern, innovation-driven data engineering organization responsible for powering one of the world's largest financial and company databases, enabling data-driven insights and supporting Moody's success in an increasingly AI-driven industry.


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