Technical Skills & Tools Inventory Questions

Be ready to discuss specific tools and platforms you're familiar with: marketing automation (HubSpot, Marketo, Klaviyo, ActiveCampaign), CRM systems (Salesforce, Pipedrive), analytics tools (Google Analytics, Mixpanel, Amplitude), data visualization (Tableau, Looker, Power BI), testing platforms (Optimizely, VWO), or data management platforms. For each tool, be specific about what you actually did (created reports, set up workflows, troubleshot issues, etc.), not just 'familiar with.' If you lack certain tools, mention your ability to learn technical systems quickly and provide examples of how you've picked up new platforms.

EasyTechnical

0 practiced

Using PostgreSQL, write a SQL query to calculate monthly active users (MAU) for the last 6 months from an events table with columns (user_id, event_name, event_timestamp). Return results as two columns: month (YYYY-MM) and mau_count, ordered newest to oldest.

MediumTechnical

0 practiced

Your company must choose between Looker and Tableau for analytics. Compare the platforms on developer productivity, self-service capabilities, governance and single source of truth, embedding and APIs, scalability and concurrency, licensing/cost, and typical team fit. Make a recommendation for a medium-sized SaaS company and justify trade-offs.

HardTechnical

0 practiced

As the new head of BI, draft a 6-month roadmap to (1) improve data literacy across the company, (2) standardize tooling and metric definitions, (3) reduce dashboard maintenance overhead by 50%, and (4) increase trust in reported metrics. Describe key initiatives, milestones, owners, KPIs to measure success, and change management steps to secure cross-functional buy-in.

HardTechnical

0 practiced

Describe how you would integrate Optimizely experiment assignment and exposure data into the analytics warehouse so you can attribute experiment impact on revenue and conversion funnels. Address capture of assignment/impression events, mapping to user identifiers, experiment metadata preservation, dealing with sampling and overlapping experiments, and ensuring data is queryable for attribution analysis.

EasyTechnical

0 practiced

How do you establish and maintain consistent metric definitions across teams so there is a single source of truth? Describe the processes, roles, documentation tools (data dictionary/metric registry), review and sign-off workflows, and how you resolve disputes when teams disagree on a metric definition.

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