Lead Product Manager, Data Platform

Lead Product Manager – Data Platform

Lead Product Manager based in the United States, owning the strategy, roadmap, and delivery of the data platform powering Alkami’s broader product strategy. This senior individual contributor role spans multiple engineering groups and product surfaces, guiding a multi‑year vision for a unified data layer and intelligence layer.

• Platform Strategy – Roadmap
  • Own and evolve a multi‑year roadmap spanning data ingestion, data modeling, and intelligence capabilities built on top of them.
  • Translate Alkami’s broader product strategy into a coherent platform strategy, ensuring the data layer is a true force multiplier for downstream product teams and client outcomes.
  • Define and champion the product vision for the unified data layer and the intelligence layer that sits on top of it, including how native, client, and third‑party data sets are surfaced through a single, consistent experience.
  • Drive a strong point of view on data governance, quality, lineage, definitions, and standards across both ingestion and modeling domains.
  • Define and monitor key business and platform metrics that measure success, and use those insights to continuously optimize delivery and value.
• Data Ingestion, Modeling & Intelligence
  • Partner with the data ingestion engineering team to deliver scalable, cloud‑native pipelines that onboard new data sources reliably, securely, and cost‑effectively.
  • Partner with the data cleansing, modeling and insights engineering team to deliver curated, high‑trust analytic models that power internal analytics and external client experiences.
  • Shape the intelligence layer roadmap in close partnership with Data Science, advancing Alkami’s machine learning capabilities from point solutions toward a coherent, reusable intelligence platform.
  • Act as the voice of the customer—synthesizing input from financial institution clients, internal analysts, and product teams—to prioritize work that maximizes platform value.
  • Own and manage backlogs for the teams you support, ensuring they are well‑organized, prioritized, and aligned with the roadmap.
• Cross‑Functional Product Leadership
  • Lead product across two cross‑functional Scrum teams (engineers, designers, QA, data scientists), driving alignment without owning the org chart.
  • Serve as the central product point of contact for Sales, Client Success, UX, Engineering, Data Science, and other Product teams that depend on the data platform.
  • Partner with peer Product Managers to ensure the data platform meets the needs of the products built on top of it and the strategic bets the company is making.
  • Lead the Agile ceremonies relevant to your teams—sprint planning, backlog refinement, sprint reviews, retrospectives—and help shape how product and engineering operate together at the platform layer.
  • Collaborate with engineering leadership to define scope, sequencing, dependencies, and resourcing across both teams.
  • Mentor and uplevel other product managers and adjacent roles through example, coaching, and clear product craft.

• Education & Experience
  • Bachelor’s degree in Computer Science, Engineering, Business, or a related field; advanced degree a plus.
  • 10+ years of product management experience, with meaningful time spent on data platforms, analytics products, or developer/internal platforms.
  • Demonstrated experience operating at a lead or principal level: setting direction across multiple teams, influencing senior stakeholders, and owning outcomes at a platform or portfolio scope.
  • Prior experience in fintech, digital banking, SaaS, or another regulated, data‑intensive domain strongly preferred.
  • Must be based in and authorized to work in the United States; this is a U.S.
    
    -based, remote‑first role.
• Technical & Domain Expertise
  • Strong fluency in cloud‑native data architectures: data lakes, data warehouses, lakehouse patterns, streaming and batch pipelines, and modern modeling approaches.
  • Hands‑on familiarity with AWS data services and the broader modern data stack.
  • Experience productizing client‑facing data and analytics capabilities, including exposing curated and client‑owned data sets through unified, analyst‑friendly experiences.
  • Sol…