Vice President, Data Management Engineer

Vice President, Data Management Engineer At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators and champions of inclusion, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We’re seeking a future team member for the role of Vice President, Data Management Engineer to join our Conventional Trust team. This role is in New York, NY In this role, you'll have the opportunity to impact our organization in the following ways: Establish partnerships with source system data owners and reporting team (data users) to understand and document requirements related to the use and gain an understanding of the data, including scope of data, limitations, attribute definitions, and linkages to other datasets. Strong Data Management, Data Modeling and Metadata Analysis skills. Analyzes application requirements and develops conceptual, logical and first-cut physical database designs (data models). Creates associated data model documentation such as entity and attribute definitions and formats. Assists in logical data designs to deliver stable and flexible high performance data solutions. Investigates and corrects data discrepancies by reconciling faulty codes. Provides data element naming consistent with standards and conventions and ensures that data dictionaries are maintained across multiple database environments (mainframe, distributed systems). Ensures data content/quality by planning and conducting moderately complex data warehouse system tests, monitoring test results and taking required corrective action. Acts as a liaison to data owners to establish necessary data stewardship responsibilities (accountability for a particular data element/verifying accuracy of the data element before loading it into the database) and procedures. Analyzes and designs data models, logical databases and relational database definitions using both forward and backward engineering techniques. Seeks opportunities to promote data sharing, and to reduce redundant data processes within the corporation by identifying common structures across application areas. Ensure adherence to data quality standards. Determine root cause for data quality errors and make recommendations for long-term solutions. Good to have knowledge on Procurement, Third-party governance and vendor data. To be successful in this role, we’re seeking the following: Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required 6-10 years of experience in software development required; experience in the securities or financial services industry is a plus The candidate should have strong understanding of big data technology stack such as Snowflake. The candidate should be a Python expert, SQL with Data Engineering capabilities. The candidate should have proven experience with RDBMS like Oracle. The candidate should have proven experience implementing AI/ML based data solutions to solve complex data management problems The candidate should be able to demonstrate their work on real world projects with nice-to-have Skills AI, ETL tools like Apache airflow , Restful API design and development, Reporting/BI tool such as Microsoft Power BI , GIT Lab CICD and JIRA. Design and develop scalable data processing workflows using Pyspark and Python Write complex and performance optimized SQL queries Perform data extraction, transformation and loading (ETL) Troubleshoot