Senior Software Engineer - Java

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

• 6+ years of experience in software development using Java with a focus on real-time data ingestion pipelines and building RESTful APIs
• Strong proficiency in Java (11+) and modern Java ecosystems
• Solid knowledge of object-oriented design, SOLID principles, and design patterns
• Experience designing microservices and scalable RESTful APIs
• Strong expertise in Apache Kafka, including delivery semantics and consumer design
• Hands-on experience with MongoDB including data modelling, indexing, and aggregations
• Hands-on experience with OpenSearch or Elasticsearch including indexing, configuration, and query tuning
• Strong understanding of data structures, algorithms, and performance optimization
• Experience with Java concurrency and parallel processing
• Familiarity with authentication and authorization standards such as OAuth 2.0, OIDC, JWT, and API keys
• Awareness of AI concepts and interest in applying AI tools responsibly in engineering workflows
• Experience with stream processing frameworks such as Flink, Kafka Streams, or Spark Streaming
• Experience with Avro and schema registries
• Familiarity with AWS services such as Kinesis Analytics, S3, and Secrets Manager
• Experience with Docker and Kubernetes
• Experience with Maven, CI/CD pipelines, and DevOps practices
• Experience with Lucene-based search features including analysis, autocomplete, and suggestions
• Basic understanding of artificial intelligence concepts with enthusiasm for learning and applying AI tools responsibly, including awareness of ethical considerations and responsible use guidelines

Education

• Bachelor’s degree in Computer Science or a related field; Master’s degree is a plus

Responsibilities

This role is responsible for designing, building, and optimizing real-time data ingestion and search pipelines within a scalable engineering ecosystem.

• Design scalable real-time ingestion pipelines using Java
• Select and evaluate data storage and search technologies including MongoDB and OpenSearch
• Propose architectures balancing performance, scalability, reliability, and cost
• Uphold clean code standards and sound software design practices
• Build Kafka-based pipelines to ingest, transform, and enrich real-time data
• Design and maintain OpenSearch indexing and ingestion pipelines
• Implement real-time data enrichment using reference datasets
• Write clean, well-tested, production-ready code
• Optimize performance, latency, and throughput under production load
• Implement secure authentication and authorization mechanisms
• Develop unit, integration, and contract tests, including Testcontainers-based testing
• Contribute to CI/CD pipelines for automated build, test, and deployment
• Apply strong problem-solving skills using optimal data structures and algorithms to deliver performance-efficient code
• Evaluate and apply AI tools to improve development efficiency and code quality
• Use AI responsibly, considering ethical and risk implications
• Understand deployment of streaming applications on cloud platforms such as AWS Managed Flink
• Collaborate with DevOps teams on Docker- and Kubernetes-based deployments
• Support system reliability through monitoring, logging, and alerting
• Follow data security and compliance best practices
• Work with product, data, and architecture teams to deliver technical solutions
• Mentor junior and mid-level engineers through reviews and design discussions
• Contribute independently to architectural and technical decision-making

About the Team

The Data Estate Engineering team drives the design, build, and operation of Moody’s Analytics’ next‑generation data pipeline. The team’s mission is to deliver high‑quality, timely data through modern, industry‑standard technologies and strong cross‑functional collaboration. As part of this team, you will contribute to large‑scale data engineering solutions and help shape how data powers Moody’s Analytics products and insights.

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.