Staff Software Engineer, Batch Processing Platform
Posted by employer 5 months ago
First seen on Joblaze 5 months ago
Last verified on the company career page 8 hours ago
Requirements
- Experience
- 6+ years
- Education
- Bachelor's degree
Not disclosed in this posting: visa sponsorship.
Benefits
Joblaze insights
- Listed about 5 months ago — first seen on Joblaze May 9, 2026. Last confirmed on Pinterest's careers page October 31, 2026.
- Salary band is in line with the typical range for Data Engineering roles (median ~$180,656).
- Starts above 14% of 21 comparable staff data engineering roles in United States that list Python we track (median $212,000 across 12 companies). See Python salary trends
- Python appears in 55.6% of 54 comparable staff data engineering roles in United States; Presto appears in 1.9% of 54 comparable staff data engineering roles in United States.
Quick facts
- Is the Staff Software Engineer, Batch Processing Platform role remote?
- It's hybrid — Pinterest expects some on-site time in Seattle, WA, US; Remote, US.
- What's the salary range?
- Pinterest lists $177,185–$364,795 for this role.
- How much experience is required?
- At least 6 years of relevant experience for this Staff Software Engineer, Batch Processing Platform role.
- Where is the role based?
- Pinterest is hiring for this position in Seattle, WA, US; Remote, US.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Iceberg, Java, Presto, Python, Scala, Spark.
- What seniority level is this role?
- Pinterest targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Staff Software Engineer, Batch Processing Platform role at Pinterest.
From the original posting
About Pinterest:
We’re looking for a Staff Software Engineer to help us build a high-performance, efficient, and easy to use batch processing platform and infrastructure at Pinterest. You’ll be working on some of the most exciting big data open source technologies such as Spark, Presto/Trino, Iceberg, etc. at the scale of hundreds of petabytes of data to bring everyone the inspiration to create a life they love.
What you’ll do:
- Design, implement, and optimize Pinterest’s batch processing infrastructure.
- Collaborate with cross-functional teams to understand data needs.
- Lead technical projects and initiatives, driving them to completion.
- Mentor and guide junior engineers on best practices and architecture.
- Ensure the reliability, scalability, and efficiency of data systems.
What we’re looking for:
- Minimum 6 years of experience building and supporting large scalable big data infrastructure/platforms
- Extensive experience with big data query technologies such as Spark SQL or Presto/Trino.
- Proven skills in designing and maintaining scalable data infrastructure.
- Proficiency in programming languages like Java, Scala, or Python.
- Strong problem-solving abilities and a drive for innovation.
- Excellent communication skills and the ability to collaborate across teams.
- Bachelor's degree in a relevant field such as Computer Science or Engineering, or equivalent experience.
In-Office Requirement Statement:
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
- This role will need to be in the office for in-person collaboration 1-2 times/quarter, and therefore can be situated anywhere in the country.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Our Commitment to Inclusion:
Standard company text repeated across Pinterest's postings is omitted here.