Vice President, Data Management Engineer

We’re seeking a future team member for the role of Vice President, Data Management Engineer to join our PAYMENTS ENABLEMENT ENGINEERING team. This role is located in Pune.
In this role, you’ll make an impact in the following ways:
Mesh Integration and Data Product Onboarding
Design and build reusable APIs, connectors and event-driven patterns for Data Product registration, validation, publication and lifecycle management.
Integrate Snowflake, Git and CI/CD pipelines with metadata, catalog, lineage, data-quality, entitlement and marketplace capabilities.
Implement metadata-as-code, data-contract and schema-validation patterns that can be adopted across platforms.
Create closed-loop integrations that synchronize identifiers, ownership, status, changes, exceptions and retirement events.
Engineer secure, scalable and supportable deployment patterns with automated testing, versioning and release controls.
Governance Automation and Controls
Translate governance, policy and certification requirements into automated validations, workflow steps and deployment gates.
Validate required ownership, classifications, descriptions, ADS linkage, lineage and data-quality controls before publication.
Automate schema-drift detection, exception routing, control evidence and certification workflows.
Design human-in-the-loop workflows that automate mechanics while preserving accountable business and risk decisions.
AI-Enabled Data Operations
Apply AI to accelerate metadata discovery, enrichment, mapping, classification and data-quality rule suggestions.
Build structured, traceable AI workflows with evaluation, guardrails, confidence thresholds and approval controls.
Develop accelerators for enterprise identifier mapping, reference-data enrichment and relationship resolution.
Measure automation accuracy and operational impact through a trust-but-verify model.
Package successful components as reusable services that can scale across Asset Servicing domains.
To be successful in this role, we’re seeking the following:
Critical Knowledge, Skills and Abilities
Strong software, data-platform or integration-engineering capabilities with a production mindset.
Deep experience designing REST APIs, event-driven integrations, data pipelines and distributed services.
Hands-on expertise with Python, SQL, Snowflake, Git and CI/CD.
Experience with metadata catalogs, lineage, data quality, schemas, data contracts or Data Product platforms.
Understanding of observability, idempotency, retries, recovery, audit logging, security and entitlement patterns.
Ability to translate governance and control requirements into testable, automated engineering controls.
Practical experience applying LLMs or machine learning to structured enterprise workflows with human oversight.
Ability to move rapidly from prototype to maintainable, production-ready capability.
Ability to work across Product, Architecture, Governance, Risk, Operations and Engineering teams.
Strong judgment and a bias toward measurable business outcomes over technology novelty.
Required Experience
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.
Experience integrating enterprise data, metadata, Reference Data, governance or Data Product ecosystems.
Experience with cloud data platforms, automated testing, deployment pipelines and operational monitoring.
Experience partnering directly with Product, Architecture, Data Governance and platform-engineering teams.
Bachelor's degree or equivalent professional experience.
Strongly preferred: Asset Servicing, Fund Accounting, Custody, Middle Office, Transfer Agency or Capital Markets experience. Experience with enterprise metadata platforms, UCM or UPM, OpenAI APIs or comparabl