# A rideshare company surfaces driver locations on a live ops map Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem 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. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-rideshare-company-surfaces-driver-locations-on-a-live-ops-09d43f97) - [System Design Interview Questions](https://datadriven.io/data-engineering-system-design) - [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep) - [Daily Challenge](https://datadriven.io/daily) --- Source: DataDriven (https://datadriven.io). 100% free data engineering interview prep. Live code execution against Postgres 16, Python 3.11, and Spark sandboxes. No paywall, no premium tier, no signup gate.