Company interview guides

Product analytics at massive scale — engagement, retention and funnel metrics.

Operational and retail metrics — orders, sellers, delivery and top-N reports.

Clean, efficient solutions — frequency counting, ranking and algorithmic Python.

Device, App Store and services analytics with a strong focus on data quality.

Telemetry, subscriptions and cloud usage — aggregations over time.

Streaming engagement, content performance and experimentation.

Two-sided marketplace metrics — hosts, guests, bookings and rankings.

Trips, drivers and surge — share-of-total and time-window questions.

Payments data — revenue rollups, growth rates and reconciliation.

Delivery logistics — orders, dashers, merchants and timing.

Professional network data — connections, job posts and engagement.

Trading and brokerage data — portfolios, trades and user activity.

CRM data — accounts, opportunities, pipeline and conversion.

Listening behaviour — streams, playlists and retention.

Short-video engagement — views, creators and virality.

Usage, tokens and API analytics with production-quality Python.

Lakehouse and pipeline work — Spark-style transforms and data modeling.

Warehouse-centric SQL — semi-structured data, performance and modeling.