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Associate Software Engineer

Heredia, Provincia de Heredia

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Date de publication
05/19/2026
ID de l'offre
13612
Niveau d'expérience
Experienced Hire
Catégorie d'emploi
Engineering & Technology
Secteur d'activité
Data Estate

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
  • 3–5 years of hands-on experience developing data pipelines using Python and PySpark to build and maintain large-scale extract, transform, and load workloads
  • Strong working proficiency with Databricks (notebooks, workflows/jobs, Delta Lake, Unity Catalog) to deliver production-grade data pipelines on a modern lakehouse platform
  • Advanced Structured Query Language (SQL) skills, including complex joins, window functions, common table expressions, and query performance tuning
  • Solid understanding of data warehousing concepts, dimensional modeling, and ETL/ELT best practices to design scalable, reliable, and maintainable data products
  • Practical experience with at least one major cloud platform (AWS, Azure, or GCP), including cloud storage, compute, and orchestration services to deploy and operate pipelines in cloud environments
  • Working knowledge of Git-based version control, CI/CD pipelines, and agile delivery practices to collaborate effectively within a distributed engineering team
  • Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
  • Strong analytical, problem-solving, and written and verbal communication skills to translate business requirements into technical solutions; prior experience with financial services, credit, or risk data is preferred
Education
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related quantitative field, or equivalent professional experience
  • Relevant certifications in Databricks, cloud data engineering, or data analytics are desired
Responsibilities
Design, build, and maintain Python and PySpark data pipelines on Databricks to deliver trusted, high-quality data products for analytics and business consumption.
  • Design, develop, and maintain scalable ETL pipelines using Python, PySpark, and Databricks to ingest, cleanse, and integrate data from internal and external source systems
  • Write, review, and tune complex SQL queries and transformations to support reporting, analytics, and downstream data consumption
  • Implement data quality checks, monitoring, logging, and alerting to ensure accuracy, completeness, and timeliness of data products
  • Partner with data engineers, analysts, product owners, and business stakeholders to gather requirements and translate them into technical specifications and working solutions
  • Troubleshoot and resolve production incidents, perform root-cause analysis, and apply performance improvements to pipelines, queries, and jobs
  • Participate in code reviews, contribute to shared coding standards, and produce clear documentation for pipelines, data models, and operational runbooks
  • Support release activities using Git, CI/CD pipelines, and agile ceremonies, delivering independently on assigned tasks while escalating complex issues when needed
About the Team
Our Data Engineering team builds and operates the cloud data platform that powers analytics, reporting, and decision-making across the organization. We partner with business lines to deliver trusted data products, enable self-service analytics, and modernize our data infrastructure on a lakehouse architecture. By joining the team, you will contribute to cloud-based data engineering, large-scale data processing, and analytics enablement, and help shape how we evaluate, adopt, and integrate AI into our data products and engineering workflows to accelerate delivery, improve data quality, and unlock new insights in a responsible and well-governed way.

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.

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