Prepare for your Databricks analyst interview

Data platform analytics, pipeline optimization, and data engineering metrics calibrated to Databricks' scale-first data culture.

Socratify AI

The Interview

What Databricks is looking for

Data Engineering Interview

Data Engineering & Pipeline Analytics

01Data Quality & Freshness

02Pipeline Optimization

03Scalability & Performance

04Cost & Efficiency Metrics

Data Analysis Interview

Lakehouse Analytics

01Data Modeling Patterns

02Query Optimization

03Analytics Architecture

04Business Impact Quantification

Data lakehouse perspective//Scale and performance obsession//Engineering rigor

Practice Library

Databricks exercises

Ready to ace your Databricks analyst interview?

Prepare for your Databricks analyst interview

Data platform analytics, pipeline optimization, and data engineering metrics calibrated to Databricks' scale-first data culture.

Socratify AI

The Interview

What Databricks is looking for

Data Engineering Interview

Data Engineering & Pipeline Analytics

01Data Quality & Freshness

02Pipeline Optimization

03Scalability & Performance

04Cost & Efficiency Metrics

Data Analysis Interview

Lakehouse Analytics

01Data Modeling Patterns

02Query Optimization

03Analytics Architecture

04Business Impact Quantification

Data lakehouse perspective//Scale and performance obsession//Engineering rigor

How It Works

Master Databricks Analyst Interviews

Data engineering and analytics cases, scored on Databricks' evaluation dimensions. · Click to expand

1Your Analyst Goals

Metrics Decomposition

Practitioner

Root Cause Analysis

Practitioner

2Analyst Case Prep

A lakehouse pipeline has 12-hour latency degradation. Data size is stable, query...

CASE INTERVIEWHard

Databricks

3Frameworks

Framework

Is customer acquisition efficiency declining?

Did paid channel efficiency deteriorate?

Google Ads CPC up 47% YoY ($3.20 → $4.70); conversion flat at 2.1%

Facebook ROAS down 38% YoY (was 3.2x, now 2.0x); CPM up 26%

Did organic/viral growth decline?

Referral rate dropped from 18% to 11% of new users (MoM -1.2pp trending)

Content marketing leads down 23%; SEO traffic flat 8 months

Did customer cohort quality or payback period change?

Did LTV decline for recent cohorts?

Recent cohort (last 90d) month-3 retention: 52% (vs historical 65%)

Median customer lifetime: 14 months (was 17mo YoY ago); LTV compression -18%

Did segment mix shift to lower-value customers?

SMB segment (< $10k ARR) now 56% of new signups (was 42% YoY ago)

SMB avg LTV: $3,100 (vs Enterprise $8,400); SMB payback: 18 months vs 11 for Enterprise

Is pricing or monetization strategy misaligned?

Did Average Revenue Per User decline?

ARPU decreased from $320 to $287 YoY (-10%); driven by downgrade cohort

Expansion revenue flat; customers not upgrading from Starter to Growth tier

Did net retention or churn deteriorate?

Monthly churn rate: 4.2% (was 3.1% YoY ago); cohort churned 32 basis points higher

Net retention (existing book): 94% (was 103% YoY ago); NRR-1 = -9pp

4Feedback

Metric Selection & Definition

Distinctive

Hypothesis Decomposition

Strong

Data Investigation

Meeting Bar

Business Impact Quantification

Strong

Repeat

Practice Library

Databricks exercises

A lakehouse pipeline ingests 500TB daily but query latency is degrading. Diagnose the...

LEARNMedium

Analytics · Pipeline OptimizationDatabricks

Design a data quality framework for a multi-tenant data platform. What metrics would you...

LEARNMedium

Analytics · Data Quality StrategyDatabricks

A customer wants to migrate from data warehouse to lakehouse. How would you measure...

CASE INTERVIEWHard

Analytics · Lakehouse StrategyDatabricks

Tell me about a time you optimized a data pipeline. What was the impact?

BEHAVIORALMedium

Behavioral · Performance OptimizationDatabricks

How would you think about the total cost of ownership for a data lakehouse vs...

BEHAVIORALHard

Behavioral · Cost & EconomicsDatabricks