Allowed R6 · Within policy
{
"slug": "data-engineering-concepts",
"title": "Data Engineering Concepts Interview",
"difficulty": "medium",
"tags": [
"data",
"devops",
"technical",
"data-eng"
],
"is_free": true,
"locked": false,
"frequency": 0.5,
"last_reported_at": "2025-09-20T12:14:22.703991Z",
"url": "https://www.mokabla.com/en/c/vezeeta/data-engineering-concepts",
"agent": {
"page": "https://www.mokabla.com/agent/en/c/vezeeta/data-engineering-concepts",
"question": "https://www.mokabla.com/agent/_call/get_question?company=vezeeta&question=data-engineering-concepts"
},
"company": {
"slug": "vezeeta",
"name_en": "Vezeeta"
},
"body_md": "## What they ask\n\nA one-hour interview for data engineering roles built around tools and concepts, and around how you communicate them. Reported prompts:\n\n- Describe a project you worked on and every tool and technology used in it, end to end.\n- Data warehouse vs data mart: definitions, when you build each, and how they relate to a lakehouse.\n- What you know about Docker and Kubernetes, and how you would containerize a scheduled pipeline.\n- Cloud services you have used for storage, orchestration and querying.\n- Batch vs streaming, and how you would design a nightly pipeline that loads bookings into a reporting model.\n- SQL questions on window functions and slowly changing dimensions.\n\nCommunication and presentation skills are explicitly evaluated: speaking clearly, confidently and concisely counts.\n\n## What they look for\n\n- A coherent architecture story for your own project (sources, ingestion, transformation, serving, monitoring).\n- Correct, crisp definitions for warehouse and mart, with a real example of each.\n- Enough container and orchestration knowledge to deploy a pipeline, not necessarily to run a cluster.\n- Concise answers; rambling costs points in this interview by design.",
"follow_ups_md": "- How would you backfill six months of data without blocking the nightly run?\n- What would you monitor to catch a silently broken pipeline?",
"access": "Question bodies are paid content: a person buys 30 days of access per company (200 EGP or 200 points) in the human app. Agents get titles, tags and difficulty; bodies only for free questions."
}