Staff Product Manager - Pipelines & Orchestration

Snowflake Snowflake · Data AI · WA-Bellevue, United States · Product Management

Staff Product Manager for Snowflake's next-generation pipelines and orchestration platform, focusing on evolving Snowflake Tasks into a full end-to-end orchestration system for data engineering, ML, and AI workloads. The role involves defining product vision, driving the roadmap, and delivering a unified orchestration experience, combining greenfield platform building with scaling an established product.

What you'd actually do

  1. Define and drive the product vision and roadmap for pipelines and orchestration in Snowflake
  2. Evolve Snowflake Tasks into a full-featured orchestration platform supporting complex workflows and dependencies
  3. Simplify how customers build pipelines by moving toward declarative, native orchestration models
  4. Partner closely with data engineering, ML/AI teams, and other platform groups to deliver end-to-end solutions
  5. Drive adoption and growth of existing capabilities while identifying new opportunities for expansion

Skills

Required

  • 8+ years of product management experience (or equivalent experience in data platforms or engineering leadership)
  • Strong background in data pipelines, orchestration, or data infrastructure
  • Proven ability to build platform products, not just features
  • Proven ability to operate in 0→1 and scaling environments
  • Strong technical fluency (SQL, distributed systems, or data processing concepts)
  • Experience working with data engineering, ML, or AI workflows
  • Ability to operate as a highly autonomous owner in a complex, cross-functional environment
  • Excellent communication and stakeholder management skills

Nice to have

  • Experience with Airflow, Dagster, DBT, or similar tools
  • Experience building developer platforms or internal tools
  • Familiarity with modern data stack architectures
  • Background in AI/ML pipelines or workflows

What the JD emphasized

  • full end-to-end orchestration system
  • Define the future of data pipelines
  • 0→1 + scale
  • End-to-end ownership
  • Build platform products
  • Operate in 0→1 and scaling environments
  • highly autonomous owner
  • Background in AI/ML pipelines or workflows