Back to Data Engineering
About this interview
A technical interview on Workflow Orchestration, pitched at the medium level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.
What you'll be assessed on
Explain what a DAG is in the context of workflow orchestration and why acyclicity matters
Compare major orchestrators (Airflow, Prefect, Kestra, Dagster) on key dimensions: scheduling, backfill, observability
Describe how to handle task dependencies, retries, and SLA monitoring in a production pipeline
Explain idempotency as a design requirement for pipeline tasks and how to achieve it
Topics covered
Orchestration fundamentalsDAG fundamentalsSchedulingTask dependenciesIdempotencyRetries and resilienceAirflowPrefectKestraDagsterTool comparisonSLA monitoringObservabilityConcurrency
A few sample questions
Just examples to set expectations - the real interview has many more and adapts to your responses.
“In plain terms, what does a workflow orchestrator actually do for a data pipeline? Why not just run scripts with cron?
“What is Prefect, and how does its approach to defining and running flows differ from Airflow's DAG model?
“What is parameterization in workflow orchestration, and how does passing a logical date or partition key to each run help with backfilling and testing?