General Technical Tool Proficiency Questions
Familiarity and practical experience with technical productivity and analysis tools such as SQL, Python or R, data visualization platforms like Tableau and Power BI, Excel, and statistical or analytical software. Candidates should be able to describe depth of expertise, typical use cases, examples of real world applications, automation or scripting practices, and how they select tools for different problems. This topic includes discussing reproducible workflows, data preparation and cleaning, visualization best practices, and integration of tools into cross functional projects.
MediumTechnical
0 practiced
Write a SQL query that identifies customers whose average order amount over the past 6 months is an outlier compared to their historical average. Given a table orders(order_id, customer_id, amount, order_date), flag customers where recent_avg > historical_mean + 3 * historical_stddev. Use window functions and explain handling of customers with sparse history.
EasyTechnical
0 practiced
You are responsible for daily ETL that loads sales data. List a lightweight checklist of automated data quality checks you would run after each load to ensure completeness and freshness. Include SQL examples or brief descriptions for checks like row count, null ratios on key fields, and referential integrity, and describe how you would notify stakeholders when checks fail.
MediumTechnical
0 practiced
Write a SQL-based data profiling query that returns for each column in a table: null count, distinct count, min, max, and sample of 3 values. Given table customers(customer_id, email, signup_date, country, lifetime_value), show the approach and discuss how you would scale profiling to hundreds of tables nightly.
HardTechnical
0 practiced
Technical: Write a SQL query to compute customer lifetime value (LTV) cohorted by acquisition month, using orders(order_id, customer_id, amount, order_date) and customers(customer_id, signup_date). Return cumulative revenue per customer cohort over 12 months. Explain assumptions such as churn handling and attribution windows.
MediumTechnical
0 practiced
You need to compute a 30-day rolling active user measure in Power BI using DAX. Describe the approach or write the DAX measure with consideration for performance and the Date table relationship. Explain how you would validate the measure against a SQL-derived baseline.
Unlock Full Question Bank
Get access to hundreds of General Technical Tool Proficiency interview questions and detailed answers.
Sign in to ContinueJoin thousands of developers preparing for their dream job.