Lead Product Manager, Core Data

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About the Role

We are seeking a highly technical Lead Product Manager to set the vision strategy and execution for our Data Ingestion Platform. This is a platform PM role ideal for someone who operates comfortably at the intersection of deep architectural discussions and long-range product strategy with a track record of driving measurable outcomes across complex distributed systems.

You will define the vision and roadmap for how large volumes of data from diverse sources are ingested transformed and made reliable within Klaviyos core systems. Youll work closely with engineering integration teams and downstream stakeholders to modernize legacy pipelines and build a scalable unified ingestion framework. At the Lead level youre not only executing the roadmap youre setting the direction influencing engineering leadership and driving org-wide alignment on data platform strategy. Please note this role requires 5 days/week in our Boston office.

Why This Role Matters

Data is foundational to everything Klaviyo delivers. This role sits at the heart of how that dataenters and powers the platform. Youll shape the architecture that enables reliable scalable dataingestion for years to come driving platform health reducing complexity and unlockinginnovation across the company.

If youre energized by building structure where it doesnt yet exist modernizing complexsystems and operating at the intersection of data architecture and product strategy this is ahigh-impact opportunity to define a critical platform capability at scale.

What Youll Do

• Set the Vision: Define the long-term mission charter and ownership boundaries for a newly formed team establishing clarity where ambiguity currently exists.
• Own the Roadmap: Develop and maintain a coherent high-impact roadmap that balances foundational investments with active initiatives; refine prioritization and sequencing across concurrent projects.
• Drive Ingestion Strategy: Define the strategy for ingesting large volumes of data from numerous sources; think holistically about data movement transformation and reliability at scale.
• Partner with Engineering: Partner with engineering to design ingestion systems that are scalable resilient and maintainable; navigate tradeoffs across performance latency cost and reliability.
• Accelerate with AI: Institutionalize AI and automation as force multipliers identify opportunities to reduce toil improve pipeline observability and accelerate the roadmap through intelligent tooling.
• Deliver Measurable Outcomes: Establish instrumentation and success metrics (e.g. ingestion reliability pipeline latency data freshness change failure rate) to validate impact and adjust priorities based on outcomes.
• Champion Quality & Reliability: Drive improvements in observability monitoring and operational excellence for ingestion systems; partner with SRE and platform teams to ensure reliability is built into every component.
• Scale for the Future: Identify and drive architectural simplifications that improve platform health over time; guide tooling choices that will keep the data ingestion platform sustainable and scalable.
• Build for Collaboration: Create transparency and open feedback loops with engineers engineering managers and senior leadership to ensure alignment and adoption of platform direction.

What You Bring

• Strategic Builder: Proven experience as a Lead or Senior Platform Product Manager in data infrastructure distributed systems or developer platform environments with a track record of driving velocity and reliability at scale.
• Data Infrastructure Depth: Deep understanding of data architecture and large-scale systems; experience with event-driven systems high-volume ingestion pipelines or complex data movement patterns.
• Technical Fluency: Comfort engaging in highly technical discussions around pipelines infrastructure and system evolution; ability to operate at both strategic and highly detailed technical levels.
• AI-Forward Mindset: Understanding of the transformative potential of AI in platform engineering; ability to separate hype from practical value and drive adoption of AI-forward practices.
• Metrics-Oriented: Fluency in measuring success via engineering productivity quality and reliability metrics; data-driven approach to prioritization and investment decisions.
• Influential Collaborator: Proven ability to define structure and clarity in ambiguous newly forming teams; skilled at stakeholder management across multiple technical organizations.
• Bias for Action: Thrives in fast-moving environments; balances short-term wins with long-term strategy and biases toward automation simplicity and self- service solutions.

What Success Looks Like

• Engineering teams feel they can deliver data-dependent features faster safer and with higher confidence than ever before.
• The data ingestion platform is recognized internally as reliable observable and a competitive advantage for product teams building on top of Klaviyos core data objects.
• Pipeline reliability improves incidents decrease and data freshness and quality metrics trend in the right direction even as ingestion volume grows.
• The roadmap and platform strategy are clear measurable and directly tied to Klaviyos ability to deliver customer value quickly and reliably.
• AI and automation reduce operational toil with measurable gains in engineering productivity across ingestion workflows.