Interviews Analyzed
2,847
What data analysts are actually asked in interviews.
Based on 2,847 real interview reports from data analyst candidates at top companies.
Average Prep Time
12weeks
foundations
deep
system
polish
Offers Landed
72%
Among candidates following the plan
Avg Salary Bump
+$28k
Pre-offer vs post-offer base + equity
We pull jobs from sources most job seekers never check
01 — Companies
What top companies emphasize.
Different company types focus on different aspects of data analysis skills during interviews.
FAANG
HighMeta · Google · Amazon · Apple
100%
- Algorithms 25%
- System design 35%
- Behavioral 25%
- Domain / fit 15%
Heavy emphasis on scalable analytics systems and product metrics. Expect complex SQL and statistical analysis questions.
Product AnalyticsScale
FINTECH
HighStripe · Square · Robinhood · Coinbase
100%
- Algorithms 20%
- System design 30%
- Behavioral 20%
- Domain / fit 30%
Focus on financial metrics, risk analysis, and regulatory compliance. Strong emphasis on data accuracy and business impact.
Financial ModelingRisk Analytics
EARLY-STAGE · SERIES A-B
MediumVarious startups · growth companies
100%
- Algorithms 15%
- System design 20%
- Behavioral 25%
- Domain / fit 40%
Emphasis on business impact and cross-functional collaboration. Need to wear multiple hats and work with limited resources.
Business ImpactVersatility
02 — Topics
Most frequently tested topics
68% of interviews containing topic
01
SQL & Database Queries
89%joins, window functions, aggregations, subqueries, CTEs
Complex queries involving multiple tables, window functions, and performance optimization
02
Data Visualization & Reporting
76%dashboard design, chart selection, KPI definition, storytelling
Creating meaningful visualizations and communicating insights to stakeholders
03
Statistical Analysis
68%hypothesis testing, A/B testing, regression, correlation
Applying statistical methods to answer business questions and validate findings
04
Business Case Studies
82%metric definition, root cause analysis, business impact, recommendations
Analyzing real business scenarios and providing data-driven recommendations
05
Data Quality & ETL
54%data cleaning, validation, pipeline design, error handling
Ensuring data accuracy and designing robust data processing workflows
06
Python/R Programming
61%pandas, data manipulation, automation, scripting
Writing code for data analysis, automation, and advanced statistical modeling
03 — Interview loop
The data analyst interview process
Most candidates struggle with the business case study round, where analytical thinking and communication skills are tested together. This is often the deciding factor.
Pass-rate funnel
Phone Screen · 78%
Technical Assessment · 65%
Business Case Study · 42%
System Design · 58%
Behavioral · 72%
Offer rate compounded ≈ 2.3%
01
Phone Screen
30 min · pass 78%
Basic SQL questions and resume discussion
02
Technical Assessment
60-90 min · pass 65%
Take-home SQL/Python analysis or live coding
03
Business Case Study
BOTTLENECK45-60 min · pass 42%
Analyze business problem and present recommendations
04
System Design
most candidates fail45 min · pass 58%
Design analytics infrastructure or reporting system
05
Behavioral
30-45 min · pass 72%
Leadership principles and past experience
04 — Question bank
Real questions you'll encounter.
Curated from actual data analyst interviews at top companies.
SQL QUERIES
Medium → HardMonthly retention rate
- user cohorts
- rolling averages
- churn analysis
- window functions
BUSINESS ANALYTICS
MediumRevenue drop investigation
- funnel analysis
- segment breakdown
- seasonality check
- hypothesis testing
A/B TESTING
Medium → HardExperiment design
- sample size
- statistical significance
- bias detection
- metric selection
DATA MODELING
HardCustomer LTV prediction
- feature engineering
- model selection
- validation strategy
- business impact
DASHBOARD DESIGN
MediumExecutive KPI dashboard
- metric hierarchy
- drill-down capability
- alert thresholds
- user experience
DATA PIPELINE
Medium → HardETL optimization
- performance tuning
- error handling
- data validation
- monitoring setup
892 questions in the bank
Open the full bank →05 — Prep roadmap
12-week preparation roadmap
Structured approach to master data analyst interviews, from SQL fundamentals to advanced business case studies.
Hours / week
Total: 78 hrs
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
Weeks 1-3
5 hrs/wk
SQL & Analytics Foundations
Master core SQL concepts, basic statistics, and data visualization principles. Build strong fundamentals in data manipulation and analysis.
SQL BasicsStatisticsExcel/SheetsData Viz
Weeks 4-7
6 hrs/wk
Advanced Analytics & Programming
Learn complex SQL patterns, Python/R for analysis, and statistical testing. Practice with real datasets and business scenarios.
Advanced SQLPython/RA/B TestingBusiness Cases
Weeks 8-10
7 hrs/wk
System Design & Architecture
Understand data warehousing, ETL pipelines, and analytics infrastructure. Learn to design scalable reporting systems.
Data WarehousingETL DesignPipeline ArchitecturePerformance
Weeks 11-12
8 hrs/wk
Interview Practice & Polish
Mock interviews, case study practice, and presentation skills. Focus on communication and business impact storytelling.
Mock InterviewsCase StudiesPresentationBehavioral Prep
06 — Tools & resources
Tools & resources that work.
Battle-tested by candidates who landed offers.
Mix of free + premium.
InterviewPal
Guided interview prep with mentorship and structured paths.
Best for: Structured prep
Visit InterviewPal
LeetCode
2,000+ coding problems. Premium unlocks company-tagged sets.
Best for: Algorithms & DS
Visit LeetCode
System Design Primer
Free comprehensive guide. The de-facto starting point.
Best for: SD fundamentals
Visit System Design Primer
Blind
Anonymous tech community. Real interview experiences and insights.
Best for: Real signal
Visit Blind
Levels.fyi
Salary and interview data, by company and level.
Best for: Company intel
Visit Levels.fyi
Pramp
Peer mock interviews. Live practice with real people.
Best for: Live practice
Visit PrampFrequently Asked Questions
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