Director, Product Management - Data Transformation (Frontier Engineering)
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Data Transformation is the foundational product portfolio that makes enterprise Agentic AI possible. Our mission is to transform the full enterprise data estate. We build the product that guides customers through every layer of a modern AI architecture: from Platform Foundation & Migration, through Data Ingestion & Engineering, to Semantic, Context, Ontology, & Governance layers. By unlocking each layer, we enable customers to deploy Agentic AI with full, governed access to their complete Snowflake data estate. The Data Transformation workflows are some of the most complex enterprise challenges and the most impactful for our customers and for Snowflake.
FRONTIER ENGINEERING
Sitting within Snowflake’s Frontier Engineering organization—a specialized team of Engineers, Product Managers, Solutions Architects, and AI Experts—you will own Snowflake’s Data Transformation product portfolio. Your scope spans intelligent migration products that understand and rewrite legacy application logic, multi-source ingestion pipelines, legacy data warehouse modernization, ETL/ELT transformation, and data platform rationalization. In this role, you will set product vision, lead a team of PMs, and deliver the tooling that turns fragmented legacy infrastructure into an AI-first enterprise platform.
AS A DIRECTOR OF PRODUCT MANAGEMENT, YOU WILL:
- Define Vision & Strategy: Own the strategic roadmap across the full transformation stack—from platform migration to semantic and context layers—ensuring every initiative moves enterprises closer to an AI-ready Snowflake platform.
- Lead & Scale a High-Performing PM Team: Build, mentor, and manage a team of product managers, fostering a culture of high velocity, accountability, and technical rigor.
- Partner with Engineering Leadership: Deeply engage with technical leaders to shape execution strategies, balancing engineering effort and long-term architectural scalability across complex pipeline and query transformation workloads.
- Drive Execution with an MVP Mindset: Champion speed and clarity, setting precise roadmap milestones, prioritizing ruthlessly, and ensuring seamless cross-functional alignment.
- Own GTM & Customer Adoption: Partner with Marketing, field teams, and executive customers to position transformation capabilities, accelerate migrations, and drive platform adoption.
- Drive Thought Leadership: Serve as an external voice for Snowflake, helping shape the industry narrative around legacy modernization, automated pipeline refactoring, and AI-first data architecture.
OUR IDEAL DIRECTOR OF PRODUCT MANAGEMENT WILL HAVE:
- 12+ Years in Data Infrastructure: Proven track record delivering enterprise-scale data platforms, migration tooling, query engines, or pipeline infrastructure.
- Proven PM Leadership: Strong experience building, managing, and mentoring high-performing product management teams.
- Deep Technical Foundation: Hands-on familiarity with modern data ecosystems—including SQL execution, ETL/ELT patterns, declarative pipelines, and workflow orchestration.
- Applied GenAI Exposure: Practical understanding of AI-assisted capabilities, such as automated code translation, developer co-pilots, semantic validation, and LLM-driven refactoring.
- Strategic & Analytica...
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Cloud data platform for storing, analyzing and sharing data and building AI applications.
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