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Let's begin! Associate Data Engineer - Onsite Hybrid (15496)

Moody's Corporation
Boca Raton, USA
Full-time
Mid · 2+ years experience
Hybrid
USD 78300-113550 yearly / year
Discovered 1 weeks ago
PythonPySparkScalaSQLDatabricksAWS

Full Job Posting

Skills and Competencies

  • 2+ years of experience in data engineering, building and operating production data pipelines
  • Strong hands-on experience with Python, PySpark, Scala, and SQL
  • Proven experience designing or working with configuration-driven or metadata-driven data pipelines
  • Experience working in a Databricks-based data platform, with a solid understanding of data modeling, schema evolution, and large-scale dataset management
  • Experience deploying data solutions in AWS and Azure cloud environments
  • Working knowledge of CI/CD concepts and experience integrating data pipelines into automated delivery workflows
  • Strong collaboration and communication skills, with the ability to work across global, cross-functional teams
  • 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

Preferred

Experience using dbt for data transformations, testing, and documentation

Familiarity with data governance, cataloging, and lineage tools

Experience supporting externally facing or commercial data products

Exposure to infrastructure-as-code or platform automation tooling

Knowledge of data quality frameworks and monitoring solutions

Education

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

Responsibilities

  • At Moody's, we unite the brightest minds to turn data into insight — we are seeking a Data Engineer to join our data platform organization and help enable the scalable delivery of high-quality data across the enterprise.
  • Develop and maintain scalable ETL/ELT pipelines that ingest, transform, and publish datasets across multiple data domains
  • Implement and extend configuration-based pipeline frameworks to efficiently support numerous datasets with consistent patterns and controls
  • Build data transformations and validations using Python, PySpark, and SQL within Databricks
  • Ensure data products are well-structured, performant, and optimized for downstream consumption by internal teams and external commercial clients
  • Partner with data producers, platform teams, and consumers to define data contracts, schemas, SLAs, and quality standards
  • Apply best practices for data reliability, observability, performance tuning, and cost optimization
  • Contribute to and follow CI/CD practices for data pipelines, including automated testing, deployment, and promotion across environments
  • Develop and operate data pipelines in cloud environments, with hands-on experience across AWS and Azure
  • Produce and maintain clear technical documentation for pipelines, configurations, and operational processes
  • Support data governance initiatives, including data quality, lineage, and access management

About the Team

Our Data Estate Engineering team is mission-critical, powering one of the key and most complex components of Moody's Enterprise Data Platform — CORE. We are a modern, forward-thinking, innovation-driven data engineering team that supports the largest company and financials database in the world, serving as the backbone of Moody's success today and into the AI-driven future of the financial industry. By joining our team, you will contribute to high-impact data solutions at enterprise scale, collaborating with passionate engineers across global teams who are embracing AI-enabled ways of working, automation, and continuous innovation.

For US-based roles only: the anticipated hiring base salary range for this position is $78,300.00 - $113,550.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody’s also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email [email protected] . This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Click here to view our full EEO policy statement . Click here for more information on your EEO rights under the law . Click here to view our Pay Transparency Nondiscrimination statement .

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.

Requirements

  • 2+ years of experience in data engineering, building and operating production data pipelines
  • Strong hands-on experience with Python, PySpark, Scala, and SQL
  • Proven experience designing or working with configuration-driven or metadata-driven data pipelines
  • Experience working in a Databricks-based data platform, with a solid understanding of data modeling, schema evolution, and large-scale dataset management
  • Experience deploying data solutions in AWS and Azure cloud environments
  • Working knowledge of CI/CD concepts and experience integrating data pipelines into automated delivery workflows
  • Strong collaboration and communication skills, with the ability to work across global, cross-functional teams
  • 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

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