Global Services Data & Business Analyst (Hybrid)
Posted Sep 7, 2026 · We last checked this listing on Sep 20, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
Behavioral
Describe a time you automated a manual reporting process. What tool did you use, Python, Alteryx, or SQL, and how much time or error did it actually save?
whether automation claims are backed by a concrete before-and-after
Tell me about a project where the requirements from stakeholders kept changing partway through. How did you handle it without blowing the timeline?
ability to manage scope and milestones across global, cross-functional teams
Tell me about a time you had to explain a technical or data concept to someone non-technical, maybe a senior leader, who needed to make a call based on it.
ability to translate complexity into a clear, actionable recommendation
Tell me about a time your analysis or recommendation was ignored or overridden. What did you do afterward?
resilience and whether they escalate constructively or just let it go
Technical
Walk me through a dashboard you built in Tableau that executives actually used to make a decision. What was in it and why did you make the design choices you did?
whether the candidate can build for a decision-maker audience, not just make a pretty chart
Tell me about a SQL query you wrote that was genuinely complex, maybe with CTEs, window functions, or several joined tables. What was the business question behind it?
real hands-on SQL depth versus resume keyword matching
How would you go about validating a new dataset before you trust it enough to build a dashboard on top of it?
rigor around data quality checks, not just technical skill
Have you worked with AI or machine learning outputs, like a forecast or anomaly detection model, inside a BI workflow? What was your role in that, exactly?
honest assessment of AI/ML exposure versus just having heard the terms
What is your experience with Tableau Server specifically, beyond just building in Desktop? Have you managed permissions, extracts, or refresh schedules?
depth of platform experience versus surface-level dashboard building
Situational
Say two departments each claim their own numbers are the correct source of truth and they disagree. How do you figure out which one is right, or reconcile them?
data governance instinct and how they handle politically sensitive data disputes
Imagine an executive asks for a metric that, once you dig in, doesn't actually mean what they think it means. What do you do?
willingness to push back diplomatically and protect data integrity over pleasing the requester
You're given a KPI to track for a new service offering with basically no historical data. How would you approach defining and building that metric?
comfort with ambiguity and structuring analysis from scratch
If you had a dozen manual reports landing on your desk every week and only enough time to automate three, how would you decide which ones?
prioritization skill and business judgment about where automation has the most impact
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As published by Motorola Solutions.
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