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.

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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

How candidates describe it

Real Sr. Software Engineer interview stories — retold from candidates' public write-ups, with sources.

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