Just wrapped the PayPal DE loop last month, senior-level, San Jose. Took about 4 weeks from recruiter call to offer. Sharing because I couldn't find much recent data on this.
The loop was 5 rounds: one phone screen (SQL and system design lite), then four onsites.
SQL: heavier than I expected. They wanted window functions, CTEs, and one question specifically around deduplication logic in a payment event stream. Not LeetCode-style joins, more like: here's a messy transactions table, find customers with duplicate charges within a 30-minute window. Wrote it cold on the whiteboard. Practice actual analytical SQL, not just SELECT * FROM.
Pipeline design: two rounds were entirely pipeline/architecture. One was about ingesting high-volume payment events at scale (think Kafka, schema evolution, exactly-once semantics). The other was building a fraud signal pipeline with latency constraints. I'm not sure they expect you to know PayPal's internal stack, but you should be able to talk trade-offs between batch vs. streaming, idempotency in pipelines, and monitoring approaches.
Tools that came up: Spark, Flink (mostly conceptual), Airflow for orchestration, Hive. The actual question was 'what would you use and why' not 'demonstrate mastery of this specific tool.'
Data modeling: one round was data modeling for a hypothetical merchant analytics product. Dimensional modeling (fact/dim tables), slowly changing dimensions, the usual. Know your Kimball basics.
Behavioral: two rounds mixed behavioral in. Standard STAR stuff. They asked about a time you caught a data quality issue before it hit a dashboard, and what you did when a pipeline you owned went down during a high-traffic event. Fintech-flavored, but not unusual.
Offer was around $210k TC for L5 equivalent, San Jose. Stock portion was relatively light compared to big tech but base was solid.
Happy to answer follow-ups. The SQL round is no joke, do not walk in unprepared for the analytical side.