VP, Data Workflow & Optimization—AI-Driven DataOps Leader

State Street; Boston (MA); On-site; USD 120,000 - 203,000; Full time

Job summary

State Street in Boston seeks a VP II, Data Workflow Analysis & Optimization to lead the design, documentation, analysis, and optimization of data governance and data operations workflows across business, data product, and technology domains.

This role focuses on improving data lineage, metadata management, data quality, and embedding scalable controls into modern data platforms, partnering with risk and privacy teams to ensure audit readiness and business trust.

Qualifications

• 10+ years in Data Governance, Data Management, or related disciplines.
• Experience in financial services sectors (asset management, banking, capital markets).
• Proven ability to design and manage data lineage, metadata, and governance workflows.
• Ability to translate requirements into executive-ready documentation.

Responsibilities

• Lead design, documentation, analysis, and optimization of data governance and data operations workflows across domains.
• Design future-state workflows to improve consistency, scalability, and accountability.
• Establish standard methods for workflow documentation, process mapping, and operational measurement.
• Partner with global stakeholders to standardize data-related processes across domains and regions.
• Drive data lineage, metadata management, and evidence production.
• Support platform tooling and AI enablement to reduce manual work and improve decision support.

Skills

Data governance

Stakeholder management

Executive communication

Process optimization

Education

Bachelor's degree in Business, Technology, Finance, Information Management, Computer Science, Engineering, or related field

Tools

Databricks Unity Catalog

Collibra

Informatica

Snowflake

Job description

State Street in Boston seeks a VP II, Data Workflow Analysis & Optimization to lead the design, documentation, analysis, and optimization of data governance and data operations workflows across business, data product, and technology domains.

This role focuses on improving data lineage, metadata management, data quality, and embedding scalable controls into modern data platforms, partnering with risk and privacy teams to ensure audit readiness and business trust.