Staff Product Manager - Pipelines & Orchestration

Snowflake
US-WA-BellevuePosted 7 April 2026

Job Description

Staff Product Manager - Pipelines & Orchestration 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. Snowflake is redefining how data is stored, processed, and activated. We are building a next-generation pipelines and orchestration platform—native to Snowflake and designed for the modern data and AI stack. We are looking for a Staff Product Manager to further evolve Snowflake Tasks into a full end-to-end orchestration system that powers data engineering, analytics, machine learning, and AI workloads. This is a high-impact, high-ownership role where you will define the product vision, drive the roadmap, and work cross-functionally to deliver a unified orchestration experience for Snowflake customers. WHAT YOU'LL DO - Define and drive the product vision and roadmap for pipelines and orchestration in Snowflake - Evolve Snowflake Tasks into a full-featured orchestration platform supporting complex workflows and dependencies - Simplify how customers build pipelines by moving toward declarative, native orchestration models - Partner closely with data engineering, ML/AI teams, and other platform groups to deliver end-to-end solutions - Drive adoption and growth of existing capabilities while identifying new opportunities for expansion - Act as the single-threaded owner (DRI) for this product area WHY THIS ROLE IS EXCITING - Define the future of data pipelines: Help move the industry beyond fragmented tools toward a unified platform - Massive impact: Own a core layer of the Snowflake platform used by thousands of customers - Proven + growing business: Work on a product area that already generates significant revenue and is growing rapidly - 0→1 + scale: Combine greenfield platform building with scaling an established product - End-to-end ownership: Operate as the sole PM with full responsibility for strategy and execution - Cross-functional influence: Collaborate across AI, ML, and core data platform teams WHO YOU ARE - 8+ years of product management experience (or equivalent experience in data platforms or engineering leadership) - Strong background in data pipelines, orchestration, or data infrastructure - Experience with Airflow, Dagster, DBT, or similar tools is highly valuable - Proven ability to: - Build platform products, not just features - 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 BONUS POINTS - Experience building developer platforms or internal tools - Familiarity with modern data stack architectures - Background in AI/ML pipelines or workflows ABOUT SNOWFLAKE Snowflake enables every organization to mobilize their data with the Snowflake Data Cloud. Customers use Snowflake to unify data, build data applications, and power AI-driven insights—all on a single platform. We are investing heavily in data engineering and orchestration to make Snowflake the best place to build and run data pipelines at scale. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must ... (truncated, view full listing at source)
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