(Senior) Data Engineer (ML, Big Data)

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. 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.

Proficiency in designing and implementing scalable, fault-tolerant data infrastructure on AWS using services such as AWS Redshift, RDS, Glue, EMR, and other related tools.

• Advanced skills in Python, PySpark, and SQL for efficient data manipulation and processing.
• Familiarity with big data technologies (e.g., Apache Spark, Hadoop) and real-time data processing solutions.
• Experience with data modelling and database design (SQL and NoSQL).
• Understanding of data governance, data quality, and security best practices.
• Knowledge of data streaming technologies such as Kafka, AWS Kinesis, or equivalent.
• Ability to work directly with data scientists, analysts, and cross-functional teams to understand business requirements and translate them into technical solutions.
• 5+ years of experience in developing and managing large-scale data infrastructure and AI applications.

Bachelor's degree (Mandatory): Computer Science, Software Engineering, Data Science, or a related field.

Master’s degree (Preferred): In a related field, contributing added knowledge.

Certifications : AWS-related certifications (e.g., AWS Certified Data Analytics) or equivalent cloud platform credentials are highly desirable.

As a Senior Data Engineer, you will play a pivotal role in designing, building, and maintaining reliable data infrastructure, including pipelines and workflows that support business functions and advanced analytics. This role is crucial in ensuring the seamless integration and operation of our AI and data infrastructure. Design, implement, and maintain robust, scalable, and fault-tolerant ETL/ELT processes leveraging AWS services (e.g., Redshift, RDS, Glue, EMR).

Develop and optimize data workflows using Python, PySpark, and SQL, ensuring top performance.

Work closely with data scientists, analysts, and stakeholders to gather data requirements while delivering effective solutions.

Ensure adherence to best practices related to data governance, quality, and security across all data pipelines.

Automate and optimize data processing tasks to improve reliability and reduce manual intervention.

Drive adoption of emerging big data technologies, cloud engineering, and automation practices.

Moody’s Ratings’ AI Analytics group develops advanced machine learning (ML) and generative AI solutions for high-profile data science initiatives. The successful candidate will guide teams in building robust, scalable, and secure solutions on AWS.The successful candidate will strive to meet Moody’s values: openness, diversity, inclusivity, respect, and a willingness to learn.

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.