Staff Software Engineer, Infrastructure Data Engineering

Pinterest is hiring a Staff Software Engineer to build reliable data systems that help teams understand and manage infrastructure usage and cost. The role leads design and hands-on delivery of pipelines, models, and services supporting infrastructure planning, cost attribution, and budget workflows.

Responsibilities:

• 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

Requirements:

• 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
• 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