Senior Software Engineer - Data Engineering
Cape Analytics
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.
Skills and Competencies
5–8+ years of hands‑on experience developing large‑scale, cloud‑native data systems.
Strong proficiency in Python, PySpark, and SQL for data processing, transformation, and automation.
Experience designing and maintaining ETL/ELT pipelines using Airflow, dbt, and Snowflake.
Proficiency with relational and NoSQL databases such as PostgreSQL, DynamoDB, and Snowflake.
Familiarity with big data and streaming technologies including Spark, Hadoop, Kafka, or Kinesis.
Strong understanding of data modeling, data warehousing, data governance, and data quality principles.
Ability to work closely with data scientists, analysts, and cross‑functional engineering partners to translate business needs into scalable technical solutions.
Strong communication, documentation, and problem‑solving skills, with the ability to mentor peers and promote engineering best practices.
Education
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
AWS certifications such as Data Analytics or Solutions Architect are a plus.
Responsibilities
Design, develop, and maintain scalable, fault‑tolerant data pipelines using AWS, Python, PySpark, Snowflake, Airflow, and dbt.
Build robust data ingestion, integration, and transformation workflows across structured and unstructured data sources.
Optimize SQL queries, processing jobs, and data models for performance, scalability, and cost efficiency.
Ensure data quality, reliability, and availability through testing, validation, automation, and observability best practices.
Support modernization and cloud transformation initiatives for next‑generation content and data delivery platforms.
Monitor, troubleshoot, and enhance the performance and reliability of data pipelines and supporting infrastructure.
Participate in code reviews, documentation updates, architectural discussions, and team knowledge‑sharing sessions.
Collaborate with product, data, and engineering stakeholders to deliver high‑impact, enterprise‑scale data solutions.
About the Team
Senior Software Engineers in Data Engineering at Moody’s build and optimize the cloud‑native data platforms that power analytics, AI, and global content delivery. They develop scalable pipelines, modernize data systems, and ensure data quality, reliability, and performance across distributed environments.
They work closely with product, data, and engineering teams to deliver secure, resilient, and high‑value data solutions—advancing Moody’s mission to deliver clarity, insight, and confidence in an increasingly data‑driven world.
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.