A rideshare company surfaces driver locations on a live ops map
A medium Pipeline Design mock interview question on DataDriven. Practice with AI-powered feedback, real code execution, and a hire/no-hire decision.
- Domain
- Pipeline Design
- Difficulty
- medium
Interview Prompt
A rideshare company surfaces driver locations on a live ops map. Driver phones publish GPS pings to a Kinesis stream every 3 seconds, and an ops dashboard polls the latest location per driver every second. The canvas has the Kinesis source; the rest of the canonical streaming shape this section just walked through is missing. Trace one event from the source through the pipeline and add: a streaming consumer process (Flink, Spark Structured Streaming, Kafka Streams, or Beam) that reads events as they arrive (plain Spark and dbt are batch tools and do not satisfy the streaming engine role), a serving store the dashboard can poll for the latest location per driver, and the live ops dashboard consumer. Tag every downstream node with a real-time-tier slaFreshness (real-time or < 1min) so the diagram makes the rhythm visible. Nothing on this canvas runs on a schedule.
How This Interview Works
- Read the vague prompt (just like a real interview)
- Ask clarifying questions to the AI interviewer
- Write your pipeline design solution with real code execution
- Get instant feedback and a hire/no-hire decision