Senior
Build scalable Spark/Scala data pipelines for Pinterest's CTV ad platform, tvScientific
Interview for a Senior Data Engineer IC role within tvScientific, Pinterest's CTV performance-advertising platform. Expect deep Spark/Scala and AWS data-infrastructure system design, SQL depth, and Pinterest's stated AI-collaboration interview philosophy where explaining your reasoning matters as much as the answer.
Step into this interview
Free · a live voice mock calibrated to this exact role
Likely format
Pinterest's process explicitly incorporates AI-collaboration evaluation — be ready to explain your reasoning and approach, not just your final answer, per their published AI interview philosophy.
What this interview tests
- Spark and Scala data infrastructure
- AWS data engineering (storage, compute, scaling)
- SQL for data manipulation/extraction
- Fault-tolerant batch and streaming pipeline design
- Critical evaluation of AI-assisted work
Common question themes
Design a fault-tolerant batch and streaming data pipeline in Spark/Scala on AWS
How would you choose a storage format (Iceberg, Delta, or other) for a fast-growing dataset
Walk through a time you optimized a data pipeline for scale
How do you verify or critically evaluate AI-assisted engineering work
Experience with data governance, data quality, or access controls in adtech-like environments
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