Define and manage the product roadmap for data governance capabilities including, data quality, profiling, and incident response systems.
Partner with engineering and data platform teams to translate data quality requirements into technical specifications, user stories, and acceptance criteria.
Lead the design and implementation of AI-powered data quality tools, such as the Data Quality GPTs, which enable users to interact with metadata using natural language for faster system understanding, field mapping and SQL query generation.
Oversee the development of next-generation data quality solutions leveraging Vector Stores, Knowledge Graphs, and Retrieval-Augmented Generation (RAG) architectures to enhance traceability and transparency across data systems.
Maintain and prioritize JIRA backlogs for governance development initiatives, ensuring alignment with strategic priorities and stakeholder needs.
Drive the build-out of governance tools and platforms, making strategic decisions between build, buy, and integration approaches.
Develop, document, and promote data quality standards, policies, and best practices across the organization.
Collaborate with data stewards, business units, and compliance teams to understand requirements and ensure governance solutions meet operational needs.

A bachelor's or master's degree in Computer Science, Information Systems, Data Science, Business, Engineering, or a related field.
At least 10 or more years of experience in data quality data management, or data platform development, with a proven track record of delivering solutions.
Minimum 5 or more years of experience in product ownership or product management roles, preferably with technical products or platforms.
Proven experience managing technical products with demonstrated ability to balance business needs, technical constraints, and user experience.
Deep knowledge of data governance frameworks, including cataloging, lineage, quality, reconciliation, profiling, and metadata management.
Strong understanding of agile methodologies, JIRA, and software development lifecycle with ability to work effectively with engineering teams.
Familiarity with data platforms, cloud architectures, and governance tools such as Collibra, Atlan, Alation, AWS DataZone, or similar solutions.
Experience developing or managing AI-driven data solutions, including natural language interfaces and advanced lineage tracing.
Familiarity with technologies such as Vector Stores, Knowledge Graphs, and RAG architectures.

VP, Product Management – Data Quality

Key skills