Software Engineer (Data Analytics & Engineering)
Posted Updated
Description
- We’re looking for a Software Engineer II, Data Analytics and Engineering to improve the quality, reliability and velocity of data science and product development at Pinterest
- You’ll build scalable data foundations, analytics tooling and analysis pipelines that enable trusted, self-service access to datasets, insights and metric investigations across cross-functional teams
- 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
- 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
- Bachelor’s degree in a relevant field such as Computer Science, Statistics, Mathematics or a related discipline, or equivalent experience
- 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
- Minimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environment
- 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