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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. 

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. 

We are seeking a dynamic and experienced Data Engineering Lead to spearhead our efforts in transforming and optimizing our extensive data assets for use with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. This pivotal role involves extracting and transforming entity-level data, distributing large datasets across various platforms, and managing bulk data feeds in multiple formats. The successful candidate will lead a team of contractors and full-time engineers, collaborate with data scientists and analysts, and ensure the efficiency, scalability, and maintainability of our data pipelines. With a strong background in data engineering, proficiency in Python and SQL, and experience with diverse data formats and platforms, the ideal candidate will drive innovation and excellence in our data management processes.

Key Responsibilities:

• Data Extraction and Transformation: Extract and transform entity-level data into formats suitable for LLMs and RAGs.
• Data Distribution: Make large datasets available across various distribution platforms, including SFTP, data marketplaces, and Databricks Delta Sharing.
• Bulk Data Feeds: Create and manage bulk data feeds in multiple formats such as delimited text, JSON, Parquet, Avro, etc.
• Team Management: Manage a team of contractors and build a team of full-time engineers as the project progresses towards completion.
• Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Optimization: Ensure data pipelines are efficient, scalable, and maintainable.

Required Skills and Experience:

• Experience: 5-10 years of experience in data engineering or related fields.
• Programming Languages: Proficiency in Python and SQL.
• Data Formats: Experience with various data formats including delimited text, JSON, Parquet, Avro, etc.
• Data Platforms: Familiarity with data distribution platforms such as SFTP, data marketplaces, and Databricks.
• Data Engineering: Strong understanding of data extraction, transformation, and loading (ETL) processes.
• Team Leadership: Proven experience in managing a team of contractors and building a team of full-time engineers.
• Problem-Solving: Excellent analytical and problem-solving skills.
• Communication: Strong verbal and written communication skills.

Preferred Qualifications:

• Experience with LLMs and RAGs: Understanding of how to prepare data for machine learning models and retrieval-augmented generation systems.
• Big Data Technologies: Experience with big data technologies and tools.
• Cloud Platforms: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

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.