Let's begin! AVP Mgr-Data Engineering

Moody's Corporation•Charlotte, NC

9h•Onsite

About The Position

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.

Requirements

Requires a Bachelor’s degree or foreign equivalent in Computer Science, Engineering or a related technical field plus five (5) years of progressively responsible experience as an Engineer, Developer, or Technical Associate/Consultant/Analyst, or in a related position performing software development and designing technical solutions.
Must have experience with designing, developing, and maintaining data integration/ETL data pipelines from various data sources and data formats.
Must have experience implementing and applying knowledge of data quality best practices and data governance principles.
Must have experience implementing, managing, supporting, and developing with AWS database and cloud technologies.
Must have experience using development languages and technologies, including Git (Bitbucket or GitHub), Jira, and Postman.
Must have experience working with DynamoDB, SQL, and Python.
Must have experience working with NoSQL, and JSON Structures.

Responsibilities

Lead, mentor, and inspire the data engineering team in the design and implementation of robust, fault-tolerant data pipelines using AWS services such as Glue, Kinesis, Lambda, and EMR.
Establish and uphold best practices for developing and optimizing efficient data processing workflows in Python and SQL.
Oversee the construction and ongoing refinement of ETL/ELT processes for both structured and unstructured data sources.
Collaborate with data scientists, analysts, and business stakeholders to clarify data requirements and deliver innovative, scalable solutions.
Champion data quality, integrity, and security at every stage of the data lifecycle.
Drive the implementation of data governance, monitoring, and automation initiatives across the team.
Provide strategic oversight and hands-on support for troubleshooting and optimizing data pipeline performance and reliability.
Design, develop, and maintain scalable data pipelines.
Support and contribute to continuous improvement, tuning, applications, infrastructure developments, process controls, and upgrades of data platform.
Provide guidance, hands-on development, and operational support for deployment of database scripts and changes across multiple environments.
Collaborate with technical teams and business owners as needed during design and implementation.
Debug and fix production report failures to ensure seamless report delivery.
Assist with performing data analysis, data cleansing, and data wrangling from various data sources.
Design and develop reports, and perform testing and data validation, data analysis, and data quality checks.
Optimize existing reports and address long running queries to deliver reports on time.
Provide solutions/inputs to improve quality of deliverables and implement processes to improve efficiency.
Collaborate with crossfunctional teams to understand data requirements and implement effective solutions.
Follow best data engineering practices, including performing analysis, requirement specification, design, development, testing, and implementation.
Deliver assigned tasks and/or specific tracks of the solution on time, escalating issues when appropriate, and mentor junior team members, including performing code reviews, conducting workshops, and reviewing documentation.