San Francisco, CA, US; Remote, US (United States) · Remote
Full-time
Mid level
6 months ago
Verified apply link — checked 4 hours ago
Salary undisclosed
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Data Product Platform is mission-critical to accelerating data-driven decision-making at Pinterest on the foundation of 100s of thousands of tables and an exadata-scale data warehouse. We strive to provide effortless, efficient, and reliable data products and platforms that power the entire company. We achieve this by investing in three core areas: Data Warehouse: Building and managing the foundational data warehouses that enable key analyses across both our core engagement and monetization products. Analytical Velocity: Creating powerful analytical tools that empower internal data users to leverage our vast data assets and capable infrastructure effectively. Data Governance: Defining and implementing the data governance policies and tools necessary to ensure the responsible, efficient and compliant storage and handling of all data. We are seeking a Sr. Staff Software Engineer to provide technical leadership and direction across these three pillars. In this role, you will be instrumental in architecting and driving solutions that handle increasing data volume, navigate business complexity, accelerate analytical velocity, and build the foundation for our next generation of AI analytics products. If you are passionate about building world-class data ecosystems at massive scale, we invite you to lead our efforts. What you’ll do: 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. What we’re looking for: 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 e
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