Staff Software Engineer, Big Data Storage

Pinterest•Palo Alto, CA

2d•$177,185 - $364,795•Hybrid

About The Position

We’re looking for a Staff Software Engineer to help build the next generation of Pinterest’s big data storage platform. You’ll work on some of the most exciting big data open source technologies — especially Apache Iceberg — at exabyte scale to power the data infrastructure that helps Pinners discover and do what they love. As a Staff Software Engineer, you’ll serve as a technical leader and hands-on contributor, designing and building highly scalable storage systems for Pinterest’s data lake. You’ll partner closely with teams across data, ML/AI, analytics, and infrastructure to evolve our storage and metadata management capabilities, enabling efficient, reliable, and governed access to data at massive scale.

Requirements

8+ years of relevant industry experience designing and building large-scale production distributed systems.
Strong experience designing and maintaining scalable storage, metadata, or data lake infrastructure.
Experience building storage capabilities for large-scale ML/AI or analytics workloads, including high-throughput data access, schema evolution, and large-scale column backfills.
Deep knowledge with building distributed systems, data storage systems, and production infrastructure.
Experience with big data technologies such as Apache Iceberg, Spark, Flink, Presto/Trino, Hive, or similar systems.
Proficiency in programming languages like Java, Scala, or Python.
Proven ability to lead complex technical initiatives and influence architecture across teams.
Strong collaboration, communication, and problem-solving skills, with a drive for technical excellence and innovation.
Bachelor’s degree in a relevant field such as Computer Science, or equivalent experience

Responsibilities

Design, implement, and optimize Pinterest’s exabyte-scale data lake storage platform.
Lead complex technical projects and initiatives for data lake storage and metadata management, driving them from architecture through execution.
Collaborate with stakeholders and partner teams across the organization to design storage and metadata layer technologies that unlock big data and ML/AI innovations.
Build storage capabilities that efficiently support large-scale ML/AI workloads, including high-throughput data access, schema evolution, and large-scale column backfills.
Shape the long-term technical direction for scalable, reliable, and efficient big data storage systems.
Engage with and contribute to open source communities such as Apache Iceberg, Spark, and Flink to help address Pinterest’s scaling challenges.