Vice President, Database Engineer

BNY Mellon

2d•Onsite

About The Position

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, Database Engineer to join our Fund Accounting and Admin team. This role is located in Boston, MA

Requirements

Bachelor's degree in Computer Science, Information Technology, or a related field
5+ years of experience with Oracle and exposure to Snowflake (or similar cloud data platforms)
PL/SQL development and advanced SQL skills
Strong data engineering capability with real-world, production-grade delivery experience
Experience with AI Agentic Workflows and Automation.
Hands-on ability to build scalable workflows using Unix, PL/SQL, and Python
Experience building and optimizing batch pipelines running in Unix/Linux environments
Ability to write complex, performance-tuned SQL (execution plans, indexing awareness, tuning approach)
Practical experience with ETL (extraction, transformation, load, controls, audit, restartability)
Proven ability to handle large datasets with strong focus on data quality, reconciliation, and reliability
Strong troubleshooting skills for batch failures, data issues, and performance bottlenecks
Comfortable working with cross-functional teams to understand requirements and deliver solutions
Follows coding standards, best practices, and maintains documentation
Strong scripting knowledge: Shell scripting + good Unix command-line understanding
Must have RESTful web service experience.
Understand microservices based, scalable architecture (previous experience working with Kafka).
Strong experience in SDLC, DevOps processes – CI/CD tools, Git, etc.
Should be capable to look into the production issue by checking code & Splunk logs
Must have: AI exposure, ETL tool , GitLab CI/CD, and JIRA experience

Nice To Haves

Experience implementing caching (using Hazelcast/ Redis) will be a plus.
Financial Services experience : Securities, Corporate Actions, Pricing, Transactions, Fund Accounting, Eagle suite of products

Responsibilities

Ensure optimal database performance and scalability by conducting regular performance assessments and implementing necessary improvements
Collaborate with software development teams to integrate database solutions seamlessly into applications, ensuring data integrity and security
Lead initiatives to enhance database automation and streamline processes, supporting BNY's commitment to innovation and operational excellence
Work closely with source system owners, reporting teams, and data consumers to gather requirements and translate them into scalable database solutions.
Understand end-to-end data flows, key entities, attributes, and relationships across upstream and downstream systems.
Convert analytical and reporting needs into logical and physical data models.
Create and maintain model documentation (ERDs, entity/attribute definitions, mapping specs, naming standards).
Develop and optimize database objects such as tables, views, indexes, materialized views, sequences, stored procedures/functions, and packages.
Apply performance tuning techniques (SQL tuning, indexing strategy, partitioning, query plans) to ensure efficient processing at scale.
Implement validation checks, reconciliation logic, and exception handling to detect and resolve data issues.
Enforce standards for data definitions and ensure consistency across environments (e.g., dev/qa/prod, multiple platforms).
Maintain data dictionaries, reference/master data rules, and metadata needed for governance and traceability.
Promote standard naming conventions, code sets, and reusable patterns.
Build/maintain database-side ETL logic and scheduling dependencies where applicable.
Monitor loads, troubleshoot failures, analyze root cause, and implement corrective actions.
Identify opportunities to improve data sharing and reduce duplicated data transformations across teams.
Contribute to data stewardship practices: definitions, ownership, access controls, and auditability.
Recommend long-term fixes for recurring data defects and performance bottlenecks.
Support changes through impact analysis, backward/forward compatibility planning, and controlled deployments