Senior BI Engineer (Hybrid)
Posted Sep 2, 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 project where you owned the full lifecycle - from a stakeholder's vague ask through scoping, building, and supporting it after launch. Where did it almost go wrong.
end-to-end ownership and honesty about project pitfalls, not just success stories
Tell me about a time you had to explain a technical limitation or tradeoff to a senior business leader who wasn't technical. How did you frame it.
ability to translate technical reality into business language for senior audiences
Describe a time you inherited or found a data pipeline or report that was technically working but poorly built. What did you do about it.
willingness to improve fragile systems and advocate for best practices, not just ship features
Technical
Walk me through a SQL query you wrote that was genuinely complex - what made it hard, and how did you make sure it stayed performant as data volume grew.
depth of real expert-level SQL experience versus surface familiarity
Tell me about a time you had to design a data mart or warehouse structure from scratch. How did you decide between a star schema and other approaches, and how did you handle slowly changing dimensions.
actual hands-on dimensional modeling knowledge, not textbook recall
What's an AI tool you've actually used in your day-to-day BI or data work, like a coding assistant or something built on Claude, Gemini, or Bedrock, and what did it change about how you worked.
genuine hands-on AI tool adoption versus buzzword familiarity
Have you worked with MicroStrategy or a comparable enterprise BI tool like Tableau or Looker? Tell me about a dashboard or report you built that stakeholders actually relied on daily.
real depth with enterprise-grade BI tools versus lightweight reporting experience
Tell me about a time your Python skills mattered for a data transformation or pipeline task that SQL alone couldn't handle well.
whether Python is a genuine working skill or just listed as nice-to-have
How have you worked with Snowflake or a comparable cloud warehouse like Databricks or Redshift at scale - what kind of performance or cost issues have you had to solve there.
specific hands-on cloud data warehouse experience at meaningful scale
Situational
Say you're building an ETL pipeline in Astronomer Airflow and a DAG starts failing intermittently in production, only during peak load. How would you go about diagnosing and fixing it.
practical orchestration debugging skills under real-world pipeline pressure
A Finance stakeholder and a Marketing stakeholder both want changes to the same dashboard, and their requirements conflict. How do you handle that conversation.
stakeholder management skill and comfort navigating competing priorities across business units
If you were asked to find new AI use cases across a business unit you didn't know well, how would you go about identifying where AI could actually help versus where it would just be noise.
judgment and initiative in driving AI adoption rather than chasing hype
You're given a request from a business owner that's really a symptom of a deeper data problem, not the actual fix they need. How do you handle that conversation without just doing what they literally asked.
requirements-gathering maturity and pushing back constructively on stakeholders
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As published by Enova.
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