Data Engineer

At Moodys, 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.

Role/Responsibilities

We are seeking a dynamic and innovative Data engineer to join our team and play a pivotal role in transforming our data pipelines from Capture Data Change, through Entity Resolution to Data mastering. If you are passionate about pushing boundaries and eager to make a significant impact, this opportunity is for you.

• Innovate and Transform: Design and implement cutting-edge, event-based data engineering pipelines to ingest, enrich, and deduplicate entities.
• Lead with Excellence: Ensure the seamless execution of an enterprise-grade operational ETL technology stack.
• Drive Impact: Gain invaluable experience in development and product releases within a fast-paced, hyper-growth environment.
• Master New Skills: Enhance your expertise with graph capabilities and entity resolution.
  
  

Requirements

• 3+ years in developing automated data pipelines using tools such as Spark, Kafka, Talend/Pentaho.
• Proficiency in data transformation operations such as mapping, cleansing, and standardization.
• Familiarity with Graph theory applied to data, and tools like Neo4J, TigerGraph, or similar. Skills on Entity Resolution or data matching topics is a plus.
• Functional knowledge of tf-idf, variance, and conditional probability.
• Working knowledge of integration patterns and CI/CD pipelines. Knowledge of Docker and K8 is a plus.
• Ability to understand, unify, and integrate internal and third-party systems using scalable data models.
• An innovative approach to tackling complex issues.