Sr. Staff Software Engineer, Data Product Platform

Pinterest is a platform where millions find creative ideas and plan for lasting memories. They are seeking a Sr. Staff Software Engineer to provide technical leadership in architecting solutions across data warehouse architecture, analytical tools, and data governance to enhance data-driven decision-making.

Responsibilities:

• Spearhead the definition and design of Pinterest's data warehouse architecture, storage, governance, and usage
• Set the strategic direction for world-class data analytics tools, including experimentation platforms, ad hoc analysis systems, data visualization, data pipeline authoring, and AI-assisted data analytics capabilities
• Define, design, and drive the adoption of comprehensive data governance policies and tooling to ensure data quality, promote responsible data handling, and maximize efficiency
• Lead ambiguous, highly challenging, and cross-functional initiatives across the data ecosystem, expertly managing trade-offs among unique requirements and constraints (e.g., usability, efficiency, and compliance) to deliver a cohesive user experience
• Drive measurable adoption and significant business impact across the entire product portfolio through platform and tooling initiatives
• Mentor and elevate the technical bar for engineers, providing leadership on complex technical design, execution strategies, and critical trade-off decisions
• Collaborate with stakeholders across Product, Data Science, and Engineering teams to understand user needs, drive alignment and drive progress

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
• 12+ years of relevant industry experience with large scale data warehouses, data tools and platforms
• 5+ years experience building data warehouses and tools around the data ecosystem with technologies such as Spark, Trino, Flink, Airflow, Querybook, Superset, DataHub, etc
• Ability to work with cross-functional partners across multiple organizations
• Hands-on experience building tools and data pipelines leveraging AI coding tools, e.g. Cursor, Claude Code, Codex, etc
• Hands-on experience building AI tools and platforms to accelerate data pipeline authoring, data analytics and engineering productivity