Data Engineer
Bengaluru, Karnataka
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, 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
From the employer’s posting
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
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
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
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field
Preferred experience
- Master’s degree in a related field, contributing added knowledge will be preferred
Qualification wording
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
Education & alternatives
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
- 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.
Tools in this posting
- Python
- SQL
- AWS
- Hadoop
- Kafka
- NoSQL
- Redshift
- Spark
- PySpark
Source — Tool mentions in context
- 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
- 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
- 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)
- 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
- 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
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.
- 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
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier listing.
- Status in our records
- Live
- First seen by us
- Oct 23, 2026 · 1 day ago
- Recorded sightings
- 6
- Last seen by us
- Oct 24, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on careers.moodys.com. The employer’s form will show what is required.
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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.
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
- 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.
Source details
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- Pay
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- Location & working pattern
Bengaluru, Karnataka
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