This role pays more than
99%
of similar roles. Most pay
$182,425–$238,837
— the shaded band above.
At the midpoint, this role pays about
$319k
versus about
$211k
for comparable roles.
Based on 240 similar postings.
Employer
About Pinterest
Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.
Pinterest currently has
82 open roles
on FindRole.
Listed pay typically runs
$164,695–$337,990
across 82 roles with salary data.
As a Sr. Staff Software Engineer on the Data Product Platform team, you will provide technical leadership across three critical pillars: data warehouse architecture, analytical velocity, and data governance. You will spearhead the design of storage systems, develop advanced analytics tools including experimentation platforms and visualization systems, and implement comprehensive governance policies to ensure data quality and compliance. The role involves managing complex cross-functional initiatives to build a foundation for next-generation AI analytics products while mentoring engineers on technical execution. You will utilize technologies such as Spark, Trino, Flink, Airflow, Querybook, Superset, and DataHub. Additionally, you will leverage AI coding tools like Cursor, Claude Code, and Codex to accelerate data pipeline authoring and engineering productivity within a large-scale data ecosystem involving hundreds of thousands of tables and an exadata-scale warehouse.
What does a Software Engineer earn in Remote?
Median $204500 from 415 postings across 57 companies.
Design and oversee Pinterest's data warehouse architecture, storage, governance, and usage.
Set the strategic direction for analytics tools including experimentation platforms and AI-assisted capabilities.
Define and implement comprehensive data governance policies to ensure quality and compliant handling.
Lead complex, cross-functional initiatives while managing trade-offs between usability, efficiency, and compliance.
Drive measurable adoption of platform and tooling initiatives across the entire product portfolio.
Mentor engineers and elevate technical standards for complex design and execution strategies.
Build AI tools and platforms to accelerate data pipeline authoring and engineering productivity.
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 of experience building data warehouses and ecosystem tools using technologies like Spark, Trino, Flink, Airflow, Querybook, Superset, and DataHub.
Hands-on experience building tools and data pipelines leveraging AI coding tools such as Cursor, Claude Code, or Codex.
Hands-on experience building AI tools and platforms to accelerate data pipeline authoring and engineering productivity.
Ability to collaborate with cross-functional partners across multiple organizations.
PostgreSQL
DynamoDB
Kafka
Flink
Spark
Delta Lake
Distributed Systems
CDC
Database Sharding
Proxy Architecture
Data Lake
Real-time Streaming
Data Ingestion
Kubernetes
EC2
Caching Systems
PostgreSQL
DynamoDB
Kafka
Flink
Spark
Delta Lake
Distributed Systems
CDC
Data Lake
Caching Systems
Database Sharding
Proxy Architecture
Real-time Streaming
Data Ingestion
Kubernetes
EC2
WarpStream