Software Engineer (Data Analytics & Engineering)

Pinterest; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Pinterest is seeking a Software Engineer II, Data Analytics and Engineering to improve data quality, reliability and velocity across data science and product development. You will 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

Qualifications

• Bachelor’s degree in CS/Statistics/Math or related field.
• 2+ years analytics engineering or data solution delivery.
• Experience building analytics pipelines and data workflows.
• Strong SQL, Python (and R) skills.
• Ability to translate partner needs into technical objectives.

Responsibilities

• Build scalable data foundations and analytics pipelines.
• Develop instrumentation and experimentation standards.
• Create tools enabling self-serve access to datasets and metrics.
• Collaborate with Product, Engineering, Data Science and BI teams.
• Use AI to accelerate analysis while ensuring correctness.
• Document datasets, metrics, and governance practices.

Skills

SQL

Python

R

AI in analytics

Data pipelines

ETL/ELT

Data governance

Education

Bachelor’s degree in CS/Statistics/Math

Tools

Airflow

Job 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 partitioningBachelor’s degree in a relevant field such as Computer Science, Statistics, Mathematics or a related discipline, or equivalent experienceDemonstrated ability to use AI to improve speed and quality in day-to-day engineering workflowsStrong track record of critically evaluating and verifying AI-assisted work through testing, data validation, source-checking or peer reviewHigh integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverablesMinimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environmentExperience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines and DAG dependencies across complex datasetsExperience translating open-ended partner needs into clear, impactful technical objectives and collaborating across Product, Engineering, Data Science, Data Engineering and Business Intelligence teams