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Databricks

Mid

Forward Deployed Engineer at Databricks (Seoul) — owning production data/AI architecture for enterprise customers

Databricks is hiring a Korea-based Forward Deployed Engineer to embed with enterprise customers and own the architecture, design, and hands-on build of production data and AI systems on the Databricks platform. The interview centers on Spark internals, cloud architecture judgment, and the customer-facing communication needed to lead technical delivery under a Korean-fluency requirement.

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What this interview tests

  • Distributed computing with Apache Spark and Spark runtime internals
  • End-to-end architecture: data pipelines + ML/AI model integration + user-facing apps
  • Multi-cloud fluency (AWS/Azure/GCP) with deep expertise in at least one
  • CI/CD for production deployments
  • Customer-facing technical delivery: scoping, stakeholder management, documentation/whiteboarding
  • Bilingual (Korean/English) communication across technical and executive audiences

Common question themes

Design an end-to-end data + AI architecture for an enterprise customer — defend your Spark and cloud choices

Tell me about a time you diagnosed a Spark performance or reliability issue in a customer's production environment

How do you scope a technical engagement with an engagement manager when customer requirements are vague

Describe how you've built a reusable accelerator or framework from a single customer project

How do you communicate a complex technical tradeoff to both a customer's engineering team and their executives

Walk me through managing conflicting priorities across multiple enterprise stakeholders

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