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
Outline a Python script (or pseudocode) that calls a paginated REST API, extracts JSON, upserts the data into a Redshift (or equivalent) table, and supports idempotent retries and logging. Describe how you'd schedule and monitor the job (Airflow or other), and how you ensure data consistency when retries occur.
EasyTechnical
0 practiced
Given a table events(user_id, event_date TIMESTAMP, revenue DECIMAL), write a SQL query using window functions to compute cumulative revenue per user ordered by event_date. Also show how you'd reset the cumulative total monthly (i.e., cumulative revenue per user per calendar month). Use ANSI SQL and show sample output columns.
MediumBehavioral
0 practiced
Tell me about a time you partnered with engineering to implement a critical business metric upstream (e.g., revenue, active users). How did you align on definitions, design tracking, set tests/QA, and agree on ownership and SLAs? Describe challenges, negotiation points, and final outcome.
MediumTechnical
0 practiced
In Tableau, you need to compute customer lifetime value (LTV) per acquisition cohort using Level of Detail (LOD) expressions. Given an orders table (user_id, order_date, amount, acquired_date), explain which LOD expressions you would use to compute per-user total revenue and then aggregate by acquisition cohort. Provide the formulas and a short explanation.
MediumTechnical
0 practiced
Propose a workflow to maintain Jupyter notebooks in Git with automated testing and deployment. Include tools and patterns (e.g., Jupytext, papermill, nbconvert, pytest, pre-commit hooks), how to split exploratory notebooks vs reusable libraries, and how to run scheduled parameterized notebooks in production.
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.