Software Engineer II, Data Analytics & Engineering

Pinterest is a platform that helps people discover creative ideas and plan for meaningful experiences. The company is seeking a Software Engineer II, Data Analytics and Engineering to build scalable data foundations, analytics tooling, and analysis pipelines that enable trusted, self-service access to datasets, insights, and metrics. The role partners with cross-functional teams to improve data quality, experimentation, product development, and data-informed decision-making.

Responsibilities:

• Develop and document practical instrumentation and experimentation standards, then partner with product engineering teams to apply them to priority product development work
• Build and improve scalable analysis pipelines and tooling that produce reliable insights at scale and strengthen understanding of key data structures and metrics
• Create tools and processes that enable Data Scientists and Engineers to independently access trusted datasets, insights and metric definitions
• Identify data quality and discoverability gaps, advocate for targeted improvements and contribute to reliable, well-governed data practices
• Maintain clear documentation for tools, datasets, metrics and operating practices to make team data assets easier to use
• Partner with Product, Engineering, Data Science, Data Engineering and Business Intelligence teams to communicate actionable insights and inform product improvements
• Use AI to accelerate analysis, prototyping and iteration, while applying judgment and verification to ensure correctness, quality and responsible use

Requirements:

• Minimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environment
• Experience using SQL and Python, R or a comparable programming language to work with large, high-dimensional datasets, including nested data structures, window functions, query optimization and data partitioning
• Experience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines and DAG dependencies across complex datasets
• Experience translating open-ended partner needs into clear, impactful technical objectives and collaborating across Product, Engineering, Data Science, Data Engineering and Business Intelligence teams
• Demonstrated ability to use AI to improve speed and quality in day-to-day engineering workflows
• Strong track record of critically evaluating and verifying AI-assisted work through testing, data validation, source-checking or peer review
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverables
• Bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics or a related discipline, or equivalent experience
• This position is not eligible for relocation assistance
• This role will need to be in the office for in-person collaboration 1–2 times per month and therefore can be situated anywhere in the country
• US based applicants only