Data Engineer

Moody's; Bengaluru; On-site; INR 1,200,000 - 3,000,000; Full time

Job summary

Moody's is seeking an experienced Data Engineer in Bengaluru to design, build, and maintain scalable data infrastructure on AWS. You will work with data scientists and analysts to implement robust ETL/ELT pipelines and ensure data governance and security.

The role emphasizes collaboration, innovation, and mentoring while advancing AI-enabled data analytics to unlock business insights. A strong background in Python, PySpark, SQL and AWS services is essential.

Qualifications

• Bachelor’s or higher in CS/Engineering or related field.

Responsibilities

• Design, build, and maintain reliable data infrastructure and pipelines on AWS.
• Develop and optimize data workflows using Python, PySpark, and SQL.
• Collaborate with data scientists, analysts and stakeholders to translate requirements into technical solutions.
• Ensure governance, quality, and security across all data pipelines.
• Automate data processing tasks to improve reliability and reduce manual effort.
• Evaluate new big data technologies and cloud engineering practices.
• Provide technical mentoring to junior team members as required.
• Foster teamwork, openness, and innovation across teams.

Skills

Python

PySpark

SQL

Data modelling

Cloud data engineering

Data governance

Data security

Communication

Leadership

Education

Bachelor's degree in Computer Science/Software/Data Science

Master’s degree in related field

AWS certifications

Tools

Redshift

RDS

Glue

EMR

Kafka/Kinesis

Hadoop/Spark

Job description

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.

Skills and Competencies

• 3+ years of experience in developing and managing large-scale data infrastructure and AI applications
• 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 along with experience with data modelling and database design (SQL and NoSQL)
• Familiarity with big data technologies (e.g., Apache Spark, Hadoop) and real-time data processing solutions
• 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
• Excellent communication, leadership, and problem-solving skills

Education

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field
• Master’s degree in a related field, contributing added knowledge will be preferred
• AWS-related certifications (e.g., AWS Certified Data Analytics) or equivalent cloud platform credentials are highly desirable.

Responsibilities

As a 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
• Provide technical mentoring and guidance to junior team members as required
• Foster a culture of teamwork, openness, and innovation within and across teams

About The Team

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.

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.