Sr. Data Product Owner, AI Engineering

KeyBank•Brooklyn, OH

2d•$96,000 - $181,000•Hybrid

About The Position

KeyBank is seeking a talented, analytical, and results-driven Data Product Owner Senior to support strategic AI Engineering initiatives within the Enterprise Data & Analytics Services (EDAS) organization. This role will own and evolve data products that enable AI-powered engineering capabilities—transforming software development signals into trusted insights that improve developer experience, efficiency, and business outcomes. The Data Product Owner Senior will apply strong strategic, analytical, and product ownership skills to guide the full lifecycle of complex data products. This role partners closely with AI Engineering, data engineering, platform teams, and business stakeholders to ensure data products are well-instrumented, governed, and adopted across the organization.

Requirements

Bachelor’s degree in Science, Technology, Engineering, Mathematics, Computer Science, or an equivalent combination of education and experience
7+ years of experience in financial services, banking, FinTech, or a related industry
Prior experience as a Product Owner or Data Product Owner, with responsibility for managing complex, cross-functional initiatives
Strong strategic, analytical, and problem-solving skills, with the ability to operate effectively amid ambiguity and incomplete information
Demonstrated expertise in requirements elicitation, documentation, and stakeholder communication across both business and technical audiences
Proven ability to lead and influence cross-functional teams, including in matrixed environments without formal authority
Experience managing multiple concurrent initiatives in a fast-paced, results-driven environment

Nice To Haves

Familiarity with software engineering data, analytics, observability, or AI-enabled development tools is a strong plus

Responsibilities

Contribute to and own the data strategy for AI Engineering–aligned data products, ensuring alignment with enterprise and line-of-business objectives
Translate engineering and business goals into clear data requirements, metric definitions, and success criteria
Oversee the end-to-end lifecycle of data products, from ideation and development through execution, adoption, and continuous improvement
Partner with AI Engineering and platform leads to define and evolve the instrumentation strategy for software development and AI-enabled capabilities
Collect, integrate, and curate data from sources such as CI/CD pipelines, code repositories, issue trackers, observability/APM tools, and service catalogs into coherent, queryable data products
Build and maintain dashboards and analytic assets that provide actionable insights for engineering teams and leaders
Promote a data-informed feedback loop to guide product direction, adoption, and ongoing optimization
Collaborate with business and technology stakeholders to prioritize quarterly and annual roadmaps aligned to business outcomes
Balance new instrumentation and feature development with data quality, coverage, and technical constraints
Manage the day-to-day execution of data products, proactively identifying risks, dependencies, and blockers
Facilitate collaboration across EDAS, AI Engineering, technology teams, and lines of business to ensure data products are effectively integrated and broadly adopted
Partner with other Product Owners across EDAS and LOBs to influence strategy and feature prioritization based on evolving data needs
Establish and uphold data governance standards, including consistent definitions, lineage documentation, access controls, and sensitive data handling
Ensure data products comply with regulatory requirements, internal policies, and privacy standards, including role-based access and appropriate anonymization