Product Manager, Data Products

The Mission

AtScale is the semantic layer for modern data and AI. We bridge the gap between complex cloud data platforms like Snowflake, Databricks, and Google BigQuery, and the business users and AI agents that need consistent, governed, AI-ready analytics. We are looking for a Senior Product Manager, Data Products to own the constructs and experiences that data engineers, modelers, data scientists, and emerging AI agents use to build data products on AtScale.

The Impact You'll Make

In this role, you will:

• Own the Modeling Surface: Lead product strategy for data modeling and ontologies, and for the modeling expression language (SML, MDX, DAX, Pandas, and others) that data engineers and modelers use to define how data behaves.
• Define the Metrics Layer: Drive the roadmap for metrics, aggregates, and advanced calculations, including how they're expressed and translated across engines like Apache Ossie, Snowflake Semantic Views, dbt, and others.
• Build for a New Kind of User: Design constructs and experiences that work as well for AI agents building and consuming data products as they do for data engineers and data scientists.
• Bridge Modeling and Consumption: Partner with engineering and architecture to keep modeling constructs, metrics definitions, and translation layers coherent as new engines and standards emerge across the ecosystem.
  
  

Why You'll Love It Here

• Ownership & Autonomy: You'll own the core modeling and metrics surface of AtScale's semantic layer, with real latitude to set direction as the category evolves.
• Innovation-First: Work at the intersection of data modeling, metrics, and AI agents at a company defining what an emerging category looks like.
• Culture of Trust: Enjoy a flexible, remote-friendly environment with in-person team hubs, built on transparency, technical rigor, and professional growth.
  
  

Who You Are

• You have 6+ years of product management experience, including significant time spent on data engineering, data modeling, metrics layers, or semantic layer products.
• You have hands-on familiarity with modeling expression languages such as SML, MDX, DAX, or Pandas, and understand the trade-offs between them.
• You understand metrics translation and semantic modeling approaches across the modern data stack, dbt, Snowflake Semantic Views, and similar frameworks.
• You've worked closely with data engineers, data modelers, and data scientists, and understand how they think about building and maintaining data products.
• You're thinking seriously about how AI agents consume and build on structured data, and what that means for the constructs product teams need to expose.
• You bring strong technical fluency—comfortable in detailed conversations with engineers about modeling, aggregation, and calculation semantics—along with excellent written and verbal communication skills.
  
  

The Perks

• Competitive salary + equity.
• Comprehensive health benefits and flexible PTO.
• The chance to define the data modeling and metrics strategy for a category-defining leader in AI-ready analytics.
  
  

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