Vice President, Data Management Engineer
BNY Mellon3 days ago
Pune, IndiaStaff+
Responsibilities
- Design and build reusable APIs, connectors, and event-driven patterns for data-product registration, validation, publication, and lifecycle management.
- Integrate Snowflake, Git, and deployment pipelines with metadata, catalog, lineage, data-quality, entitlement, and marketplace capabilities.
- Implement metadata-as-code, data-contract, schema-validation, synchronization, versioning, release-control, and automated-testing patterns.
- Translate governance, policy, and certification requirements into automated validations, workflow steps, deployment gates, and control evidence.
- Automate schema-drift detection, exception routing, certification workflows, and human-in-the-loop decision processes.
- Apply AI to metadata discovery, enrichment, mapping, classification, data-quality rule suggestions, identifier mapping, reference-data enrichment, and relationship resolution.
- Build traceable AI workflows with evaluation, guardrails, confidence thresholds, approval controls, and measurable operational outcomes.
- Package successful components as reusable services that scale across Asset Servicing domains.
- Lead a team of 8 or more and help debug and support production incidents.
Requirements
- Significant experience in software engineering, data engineering, platform engineering, or enterprise integration.
- Demonstrated experience building and operating production APIs, pipelines, automation services, or integration frameworks.
- Deep experience with REST APIs, event-driven integrations, data pipelines, distributed services, Python, SQL, Snowflake, Git, and deployment pipelines.
- Experience with metadata catalogs, lineage, data quality, schemas, data contracts, Data Product platforms, governance ecosystems, and cloud data platforms.
- Understanding of observability, idempotency, retries, recovery, audit logging, security, entitlement patterns, automated testing, and operational monitoring.
- Practical experience applying LLMs or machine learning to structured enterprise workflows with human oversight.
- Experience partnering with Product, Architecture, Data Governance, platform engineering, Risk, Operations, and Engineering teams.
- Bachelor's degree or equivalent professional experience.
- 10+ years of experience in the payment or banking industry or a related product-based company, preferably with payment-domain knowledge.
- 5+ years working in Agile/POD environments using Scrum or Kanban and 5+ years leading a team of 8 or more.
- Experience with public or private cloud concepts, production debugging, AI-based technologies such as Copilot and Windsurf, and organization-level initiatives.
- Experience in Asset Servicing, Fund Accounting, Custody, Middle Office, Transfer Agency, or Capital Markets is strongly preferred.
- Experience with enterprise metadata platforms, UCM or UPM, OpenAI APIs or comparable services, graph technologies, orchestration frameworks, and event platforms is beneficial.