Staff Software Engineer, Infrastructure Data Engineering

Remote - US Full Time Staff
US$177K - US$365K Yearly
Published on October 21, 2026
Pinterest
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Pinterest is seeking a Staff Software Engineer to build the data systems that help teams understand and manage infrastructure usage and cost. You’ll lead the design and hands-on delivery of reliable data products, including pipelines, models, and services, that support infrastructure planning, cost attribution, and budget workflows. In this individual-contributor role, you’ll shape technical direction, navigate complex cross-team work, and make infrastructure data more accurate, consistent, and useful.
What You’ll Do:
Set technical direction and help define a roadmap for reliable, scalable infrastructure data products
Design, build, and operate production ingestion and transformation pipelines, data models, and services for infrastructure usage, cost, ownership, and planning
Strengthen shared data products with clear contracts, automated quality checks, reconciliation, documentation, and operational monitoring
Lead ambiguous, cross-functional initiatives from problem definition and technical trade-offs through rollout and adoption; raise the engineering bar through mentorship and design reviews
Leverage AI to scale the impact of yourself and the team, including:
Accelerate investigation of data-quality or pipeline issues while validating findings against source data and production evidence
Speed up implementation and documentation of data transformations and interfaces while testing and reviewing the results
Explore ways to help partners self-serve trusted infrastructure insights, protecting sensitive information and verifying outputs
What We’re Looking For:
Bachelor’s degree in computer science, a related field, or equivalent practical experience
Significant experience designing, building, and operating production data systems or data-intensive services at scale
Strong software engineering skills in Python and SQL, with a record of writing tested, maintainable production code
Deep experience with ingestion, large-scale ETL and transformation, data modeling, and workflow orchestration
Experience designing data interfaces and contracts and improving quality, freshness, completeness, and consistency
A track record of leading complex technical work across teams, from framing ambiguous problems to delivery and operation
Ability to influence through technical judgment and clear communication and to mentor other engineers
Experience operating dependable data pipelines or services, including testing, monitoring, and incident response
Experience with AWS or similar cloud environments
Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
Bonus points for the following:
Experience with infrastructure cost or usage data, budgeting, shared data platforms, dbt, data lineage, or modeling hierarchical ownership
Hands-on experience with large, cloud-native multi-tenant platforms at Internet scale
In-Office Requirement Statement:
We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
This role will need to be in the office for in-person collaboration 1-2 times/month 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.
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.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only
$177,185—$364,795 USD
Our Commitment To Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.
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Skill Stack
Python
AWS
AI
Salary
$177,185 - $364,795 Yearly
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Staff Software Engineer, Infrastructure Data Engineering
Remote - US Full Time Staff
US$177K - US$365K Yearly
Published on October 21, 2026
Pinterest
@pinterest pinterest.com
We’re helping millions of people feel more inspired in their everyday lives. Join us.
What You’ll Do:
Set technical direction and help define a roadmap for reliable, scalable infrastructure data products
Design, build, and operate production ingestion and transformation pipelines, data models, and services for infrastructure usage, cost, ownership, and planning
Strengthen shared data products with clea

Work arrangement
Yes