What an Orchestrator Does

Concepts covered: paOrchestratorRoles, paRetryPolicy

An orchestrator is the system that owns four responsibilities: deciding when work runs, running it in the right order, retrying it when it fails, and showing what happened. The four are not separate features bolted together. They reinforce each other. A retry is meaningful only if dependencies are tracked. A schedule is operable only if a UI exists to inspect it. Visibility is useful only if failures are recorded as events the system can react to. Every orchestrator that ships sells the same four properties under different brands. Retries only produce the same answer as a single run when the work is idempotent: running it twice gives the same result as running it once. That property is the subject of Lesson 5 (idempotency and backfill). Responsibility 1: Scheduling The orchestrator owns wh

About This Interactive Section

This section is part of the Orchestration and Dependencies: Beginner lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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