Databricks Data Analytics Interview Questions and Answers (2026 Guide)

Quick answer: Databricks is an independent data-and-AI platform company (not a Microsoft team; "Azure Databricks" is simply the Azure-hosted, Microsoft-co-engineered edition of its product, first launched in 2017). Its India presence centres on a Bengaluru R&D hub opened in May 2023 that has since become one of the company's largest engineering sites outside the US, alongside offices in Mumbai, Gurgaon and Pune. We could not find a single Glassdoor, Blind or AmbitionBox account of a Databricks Data Analyst interview specific to India; the clearest first-hand account we found, from a US-based Blind thread, describes a Data Scientist loop built around SQL, statistics, Python and Databricks's own tools (Spark, MLflow, Delta Lake) rather than generic algorithm puzzles.

About Databricks

Databricks was founded in 2013 by the original creators of Apache Spark and is headquartered in San Francisco. It sells the "Lakehouse" data platform built around Delta Lake, Unity Catalog, MLflow and, increasingly, generative-AI tooling. Databricks remains an independent private company; "Azure Databricks" is the version of its platform that Microsoft has offered as a first-party Azure service since a 2017 partnership, jointly engineered by the two companies, not a Microsoft-built product or a Microsoft internal team. (Microsoft Azure Blog) In India, Databricks runs a Bengaluru research-and-development centre that opened in May 2023 with a founding cohort of engineers and its first intern batch drawn from IITs in Chennai, Guwahati, Kanpur, Kharagpur and Mumbai, led by Director of Engineering Rohit Ananthakrishna. (Databricks Blog) Databricks has expanded that presence since, with reporting describing India headcount approaching 1,000 by early 2026 and a committed $250 million investment in the region over three years, on top of existing offices in Mumbai, Gurgaon and Pune. (Analytics India Magazine; Databricks Office Locations)

Databricks's Interview Process

We could not find a Databricks Data Analyst or Data Engineer interview account, from India or anywhere else, detailed enough to describe stage-by-stage with confidence. What we did find, and can source, is a Data Scientist account and general engineering-hiring detail:

• Data Scientist (US-based candidate, Blind): a recruiter explicitly told the candidate the technical round "won't be leetcode, and more of data related coding," delivered through a CoderPad link. The candidate was advised to prepare data manipulation, statistics, Python, SQL and machine-learning fundamentals, and to be familiar with Databricks's own stack: Spark, MLflow and Delta Lake. A later stage included a take-home assignment using PySpark and SparkML. (Blind)

• General engineering hiring (not data-role-specific): a commonly cited shape is a recruiter screen, a technical phone screen, a hiring-manager call and an onsite loop, with Databricks's own hiring committee and reference checks factoring into the final decision. Because this pattern is documented for software-engineering hiring rather than analyst or data-science roles, we are flagging it as background context, not a confirmed data-role process. (interviewing.io)

We deliberately have not stated a Glassdoor difficulty score, percent-positive figure or average days-to-hire for Databricks Data Analyst or Data Scientist roles specifically: Glassdoor blocked our automated access to those pages directly, and the only numbers we could find came from third-party summaries we could not verify against the original candidate text, so we have left them out rather than repeat an unverified figure as fact.

What Candidates Report

• For the one detailed data-role account we could verify, the emphasis was explicitly on "data related coding" over algorithmic puzzle-solving, SQL and Python fluency, core statistics, and hands-on familiarity with Spark, MLflow and Delta Lake rather than generic machine-learning trivia. (Blind)

• Multiple general-audience prep guides aimed at Databricks interviews (not verified against real candidate transcripts) list Lakehouse architecture, Delta Lake internals, Unity Catalog governance, Delta Live Tables, medallion architecture and the Photon engine as recurring technical themes across Databricks-adjacent data roles. We are naming these as commonly cited study topics, not confirmed interview questions, since we could not trace them back to a specific candidate account. (DataCamp)

What We Could Not Verify

We looked for a Databricks Data Analyst or Data Engineer interview process specific to India across Glassdoor, AmbitionBox, Naukri Code360, Blind and general search, and found none. Glassdoor's own Databricks interview pages returned access errors on direct fetch, so any structure or statistics attributed to Glassdoor above should be read as coming from what search engines index of those pages, not text we read ourselves. We also could not confirm any current, open Databricks Data Analyst or Data Scientist requisition tied specifically to an India location; job listings we found for Databricks's own internal analytics roles could not be reloaded to confirm they were still live or India-based, so we have not cited a specific posting as current. Treat every claim above as attributed to its named source, and treat anything about "what Databricks India interviews look like" beyond that as unconfirmed.

How to Prepare

• Practise SQL and Python on realistic, messy data problems rather than pure algorithm puzzles; the one verified account explicitly distinguishes Databricks's data-role interviews from a leetcode-style bar.

• Get hands-on with Databricks's own stack: Spark (including PySpark), Delta Lake and MLflow, since a real candidate was told to know these specifically and was given a take-home in PySpark and SparkML.

• Revise core statistics and applied machine-learning fundamentals you can explain in plain language, not just implement.

• Be ready to talk about the Lakehouse architecture (Delta Lake, Unity Catalog, medallion architecture) at a conceptual level, since it is Databricks's core product and shows up across independent study guides even where we could not confirm it against a real transcript.