Lead Product Manager, Data Management

Klaviyo • Boston, MA

7h

About The Position

As Klaviyo continues to expand its data platform and invest in AI-driven capabilities, the ability to manage, govern, and structure data effectively becomes increasingly important. The Data Management and Governance team plays a foundational role in ensuring that teams across the company can build reliable products, analytics, and AI systems on top of trusted data.
In this role, you will help shape the systems that define how data is managed across the platform, enabling teams to move faster while maintaining the quality, reliability, and governance required to operate at scale.

Requirements

• 7–10+ years of product management experience, with meaningful experience building data platforms, infrastructure products, or data tooling.
• Strong technical depth with the ability to work closely with engineers on system design and architecture decisions.
• Experience working with data governance frameworks, metadata systems, semantic layers, or analytics infrastructure.
• Comfortable operating in highly technical environments involving large-scale data systems or AI/ML platforms.
• Strong analytical and problem-solving skills with the ability to define clear metrics, KPIs, and system performance indicators.
• Experience evaluating build vs. buy decisions for complex infrastructure products.
• Excellent cross-functional communicator who can align engineering, data, and product stakeholders around a shared strategy.

Nice To Haves

• An engineering or technical background is highly valued but not required.

Responsibilities

• Define and own the product vision and roadmap for Klaviyo’s data management and governance capabilities.
• Partner closely with engineering and data platform teams to design scalable systems for data governance, metadata management, lineage, and data quality.
• Drive the development of semantic data layers and modeling frameworks that simplify how teams interact with complex data systems.
• Evaluate and lead build vs. buy decisions for components of the data management stack.
• Collaborate with AI/ML teams to ensure data systems support emerging AI-powered and agent-based capabilities.
• Define and track success metrics around data quality, governance adoption, discoverability, and platform reliability.
• Lead cross-functional initiatives that improve how data is structured, documented, and accessed across the organization.
• Communicate product strategy, tradeoffs, and technical decisions clearly across engineering, leadership, and cross-functional partners.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees