Databricks Interview Questions

34 real Databricks questions asked in live technical interviews — each with a model answer. Updated weekly.

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Databricks must read tables that other tools register in Glue with Lake Formation controls. You need consistent metadata across engines. What is the right approach?🟡 Medium · Conceptual · Asked 2×Are you using Git in the project? It was integrated with Databricks. Are there any other tools you use?🟡 Medium · Conceptual · Asked 1×How do you secure data in Databricks?🟡 Medium · Conceptual · Asked 1×Why is Unity Catalog needed?🟢 Easy · Conceptual · Asked 1×Have you used Databricks?🟢 Easy · Behavioral · Asked 1×Have you worked with Databricks and Snowflake?🟡 Medium · Conceptual · Asked 1×Do you normally deploy dbt code/models from one environment to another? For example, working in a dev instance of Databricks and then moving to production. How do you manage environment variables, connections, and passwords to keep them secure and easy to manage?🟡 Medium · Conceptual · Asked 1×Another scenario I normally encounter as a data modeler: data is made available in the Gold layer and BI reports consume it, but the BI team reports that queries on the Gold layer are taking too long and they cannot get reports rendered on time. How would you handle this situation?🟡 Medium · Debugging · Asked 1×Earlier we discussed the silver layer, where we mainly write data cleansing logic using PySpark. I'm curious: would you still use Databricks notebooks and PySpark commands to create the gold layer? Are you familiar with dbt and can you execute dbt using traditional SQL templates?🟡 Medium · Conceptual · Asked 1×Do you schedule end‑to‑end flows in Databricks, for example ingesting data through an API, performing cleansing and transformations all the way to the core layer? Are these runs scheduled to execute daily or at specific intervals? If failures occur, how do you receive notifications and troubleshoot the issue?🟡 Medium · Conceptual · Asked 1×Are you familiar with Databricks?🟢 Easy · Conceptual · Asked 1×Say you have ingestion pipelines; what are you primarily using? Are you using Databricks or Snowflake? Was the whole platform considered?🟡 Medium · Conceptual · Asked 1×We are talking about a Databricks pipeline. Which pipeline did you develop, and which database did you use?🟡 Medium · Conceptual · Asked 1×Shubhi, the question is simple: When a modeler is giving a proposal to someone, should they structure the table and approach with technical rationale? Which platform are you using? In Databricks, if you are giving someone a model that works on finance data and the requirement is to maintain history, from an implementation point of view, what is the underlying architecture of Databricks?🟡 Medium · Conceptual · Asked 1×These are technology stack questions. I'm asking: When storing data, which format do you choose? In Snowflake, you can store data in native Snowflake format or Iceberg. In Databricks, you can store data in Delta Lake or Iceberg. Which format would you pick and why?🟡 Medium · Conceptual · Asked 1×Are you comfortable implementing Snowflake and Databricks with a similar model? Why would you need SCD Type 2 when implementing? Both cannot make sense if you’re leveraging either Delta Lake or Iceberg. What is the rationale to use SCD Type 2?🟡 Medium · Conceptual · Asked 1×Can you explain some use cases you have recently handled in PySpark on Databricks?🟡 Medium · Conceptual · Asked 1×If we want to move dashboards to Tableau, how should we handle transformation logic that currently resides in Remio, and how would we adjust the ingestion pipeline to load data into the raw zone in Databricks?🟡 Medium · Conceptual · Asked 1×What are the different ways available in PySpark on Databricks to handle large data ingestion scenarios, and is there a particular approach that is recommended?🟡 Medium · Conceptual · Asked 1×What options are available in PySpark on Databricks to handle scenarios involving large datasets and joins?🟡 Medium · Conceptual · Asked 1×Will using a broadcast join resolve the scenario, and can you provide the syntax for it?🟡 Medium · Conceptual · Asked 1×Between Python and PySpark on Databricks, which is more professional? If you had to choose a primary skill set, what would you pick?🟡 Medium · Conceptual · Asked 1×What is Unity Catalog and why use it?🟢 Easy · Conceptual · Asked 1×What is the difference between a normal ATL pipeline and a DLT pipeline?🟡 Medium · Conceptual · Asked 1×Why use a DLT pipeline?🟢 Easy · Conceptual · Asked 1×Did you use the auto loader option in Databricks?🟢 Easy · Behavioral · Asked 1×We have a Delta table `retail_prod.analytics.sales_silver` that is about 600 GB. It is partitioned by `event_date` (daily) and contains many small files (5–20 MB) with no Z‑Order. Dashboards filter on the last 30 days of `event_date` and `merchant_id`, and the p95 query time is above 12 seconds. We cannot change the upstream schema. How can we bring the p95 query time under 12 seconds for the 30‑day window?🟡 Medium · Conceptual · Asked 1×You need to pull 200 million rows from a source JDBC system into Databricks. The current PySpark job uses a single partition and exhausts the driver. How would you redesign the read for parallelism (choose a partitionColumn, set lowerBound/upperBound/numPartitions, handle nulls/outliers, tune fetch size) and ensure the ingest is idempotent before writing to Bronze?🟡 Medium · Coding · Asked 1×Your Databricks jobs were migrated to Unity Catalog last week. A nightly Silver write is failing because the storage credential has rotated, and you cannot change IAM roles tonight. How do you restore the write within the same window, considering Unity Catalog grants on the storage credential, external location, object ownership on `catalog.schema.table`, and job cluster access mode, while keeping auditability intact?🔴 Hard · Debugging · Asked 1×You are orchestrating a 5‑task lakehouse workflow where Task A discovers a partition path (e.g., s3://raw/yyyyymmdd=20231015) that downstream tasks must use. Finance wants ephemeral, policy‑restricted compute and parallel fan‑out where possible. Which Databricks pattern best fits?🟡 Medium · Conceptual · Asked 1×Your team wants repeatable library code for transformations across jobs and clusters. What packaging and deployment approach is most maintainable on Databricks?🟡 Medium · Conceptual · Asked 1×A Bronze-to-Silver pipeline requires data quality rules that drop invalid rows while recording metrics for monitoring. Stakeholders want declarative checks and managed lineage without hand‑coding UDF logic. Which option should you choose?🟡 Medium · Conceptual · Asked 1×You must implement near‑real‑time ingestion from S3 with schema drift (occasional new columns) while avoiding full listings of the bucket. Badly formed records should land in a quarantine column for triage. Which design is most appropriate on Databricks?🟡 Medium · Conceptual · Asked 1×Can you tell me what vacuum is in Databricks?🟡 Medium · Conceptual · Asked 1×

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