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Moody's is seeking an experienced Manager of Data Engineering to lead the design and delivery of scalable, secure data infrastructure supporting advanced analytics and AI solutions. This role sits within Moody's Ratings' AI Analytics group, which develops machine learning and generative AI solutions for high-impact data science initiatives.
You will lead a team of data engineers, providing technical guidance and supporting capability development while fostering innovation and collaboration. Key responsibilities include designing and implementing robust, scalable, fault-tolerant ETL/ELT processes on AWS (Redshift, RDS, Glue, EMR); developing and optimizing data workflows using Python, PySpark, and SQL; and partnering with data scientists, analysts, and cross-functional stakeholders to translate business requirements into technical solutions.
You will apply data governance, quality, and security best practices across data pipelines, automate and optimize data processing to improve reliability, and drive adoption of emerging big data, cloud engineering, and automation practices. The role requires deep expertise in AI implementation, with a track record of driving strategic transformation and operational efficiency. You will also manage AI-related risks, ensure ethical governance, and foster responsible AI adoption across the organization.
Required qualifications: 7+ years developing and managing large-scale data infrastructure and AI applications; proficiency in AWS services (Redshift, RDS, Glue, EMR); advanced skills in Python, PySpark, and SQL; experience with big data and real-time processing (Spark, Hadoop, Kafka, Kinesis); strong data modeling and database design skills across SQL and NoSQL; understanding of data governance, quality, and security best practices; and demonstrated leadership in managing technical teams. Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related field preferred. AWS certification (e.g., AWS Certified Data Analytics) is highly desirable.
