First thing you should do when a job candidate walks into your conference room is ask yourself, “Is this candidate better prepared for this interview than I am?” Too many companies ask candidates silly questions that a Magic Eight Ball could answer.
If that’s how you plan on acquiring a great employee, well… “Outlook Not So Good. “Don’t worry! This 90-second clip should do the trick! Will you learn how to ask better interview questions strategically? “Signs point to yes!”
When it comes time to hire new employees, many business owners ask random questions. It’s a bit like shaking the magic eight ball and then asking whatever question comes up.
We want to come up with a plan to ask the same questions of all candidates so that we can compare them.
First, you need to clearly define the traits required by the position. The personality characteristics, not the skills.
Then ask SAR questions—Situation, Action, Result. So, for example, let’s say we’re looking for the result of flexibility. We would ask the question, “Tell me of a situation in which you needed to be flexible. We would then give them a score between 0 and 10 based on their answer.
In the comments section below, please tell me what one trait you think every employee in your business should have and then give me one question about that trait that is based on a situation, action, or result.
Also, leave a question below if you want me to answer it in a future video.
What is one trait that you think every employee in your company should have? Then, share one question that is based on that trait and could be about a situation, an action, or a result.
Landing an interview at Dave means you’ve caught the attention of their talent team, But now comes the real test – showcasing your skills and experience to convince them you’re the right fit for the role
As an innovative fintech app disrupting traditional banking, Dave looks for creative problem solvers who can help enhance their cutting-edge products. For software engineering roles in particular, you can expect highly technical, hands-on assessments during the interview process.
Mastering both the technical concepts as well as translating your process clearly will be key. I’ve put together this insider’s guide covering the most common Dave software engineering interview questions so you can tackle the big day with confidence. Let’s dive in!
Overview of Dave’s Interview Process
Before we get to specific questions, here’s a quick rundown of what to expect during the different Dave engineering interview stages:
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Initial Screening Call 30 minute phone interview focused on your resume experience and interest in the role/company. Helps identify top candidates.
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Technical Screen 45-60 minute call where you’ll be asked questions testing your coding abilities technical knowledge, and problem solving skills. Aims to validate skills.
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On-site Interview: 4-6 hour in-person interview including coding challenges, architectural discussions, behavioral questions and pairing sessions with engineers. Assesses coding skills and culture fit.
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Reference Checks: Feedback on work style and strengths from professional references you provide. Validates past performance.
With this overall flow in mind, let’s explore some of the most frequently asked software engineering interview questions and tips to master them.
The Top Dave Software Engineering Interview Questions and Answers
1. Explain your experience with building highly scalable systems. What techniques did you use?
This tests your hands-on expertise with architecting and implementing high-volume, resilient systems. They’ll want to hear specifics.
Tips:
- Focus on real examples of large-scale systems you’ve worked on
- Discuss relevant methodologies like microservices, caching, etc.
- Get technical but avoid unnecessary jargon
- Highlight any quantitative impact/metrics if possible
Example: “At my last company, I was the lead engineer responsible for re-architecting our core billing system to support 10x growth over the next 3 years. To make the system resilient under high load, I transitioned our architecture to microservices, allowing us to scale components independently. I also implemented comprehensive request caching, which reduced compute needs by over 50%. Additionally, I leveraged Kubernetes for autoscaling and zero-downtime deployments. The end result was a system capable of handling 500K+ concurrent requests with 99.99% uptime, laying the foundation for rapid business growth.”
2. How would you detect and debug issues in production?
This evaluates your monitoring skills and methodical approach to diagnosing and resolving live problems.
Tips:
- Discuss implementing logging, metrics, and alerts
- Share your technical process for root cause analysis
- Show you prioritize severity when triaging
- Demonstrate a collaborative, user-focused mindset
Example: “When issues arise in production, my first focus is implementing robust observability through logging aggregation platforms like Datadog. This provides visibility into the health of all systems and services. Additionally, I set up proactive alerting based on key performance metrics like latency, error rates, and traffic spikes. This enables rapid detection. Once notified of an issue, I review aggregated logs and metrics to understand the root cause, collaborating with other engineers to brainstorm solutions if it is an unknown defect. I triage based on user impact, ensuring we address severe stability and data integrity issues first. This rigorous yet nimble approach allows us to resolve production issues promptly and minimize disruption.”
3. What techniques or principles do you follow when designing a new feature or component?
This evaluates your product design philosophy and ability to consider long-term maintainability.
Tips:
- Discuss important principles like separation of concerns, DRY, YAGNI
- Share how you gather requirements from stakeholders
- Outline considering future use cases and extensibility
- Show you prioritize simple, elegant solutions
Example: “When approaching a new feature, I start by clearly understanding product and business goals through collaborative sessions with stakeholders. I evaluate long-term maintainability by designing components to be reusable and extensible where possible. I follow principles like separation of concerns, encapsulating complex logic into services with narrow responsibilities. I leverage design patterns like command query responsibility segregation to build loosely coupled components. I also avoid premature optimization, instead focusing on clean, readable code even if that means slightly longer development time. This diligent upfront design ensures we produce high-quality features aligned to goals while maintaining simplicity, scalability and maintainability.”
4. How would you explain a complex technical concept or algorithm to someone less technical?
This tests your communication skills and ability to break down complex topics simply and clearly.
Tips:
- Convert concepts to easy analogies or visuals
- Assess their knowledge level and tailor explanation accordingly
- Watch for signs of comprehension and re-explain if needed
- Provide examples of having to simplify complex topics before
Example: “I often need to explain intricate technical concepts to colleagues with less technical backgrounds. My strategy is to use clear analogies they are familiar with. For example, when explaining how caching improves performance in distributed systems, I compare it to putting books you reference often on your office desk rather than needing to walk down to the library each time. I’ll also utilize visuals like diagrams to simplify descriptions of multifaceted algorithms. I check their understanding periodically and rephrase sections when needed. My goal is to make the information accessible and memorable rather than overly complex. My non-technical teammates often remark how much more approachable I make technical topics seem.”
5. How do you prioritize new features or technical debt work?
This reveals your product sense and ability to balance competing priorities.
Tips:
- Discuss weighing business value vs. technical risk
- Share how you collaborate cross-functionally
- Provide examples of aligning tech priorities to goals
- Show you remain flexible to changing needs
Example: “When faced with prioritizing new features versus technical debt, I always aim to take a holistic view. I collaborate closely with product managers and engineering leads to estimate business value, implementation complexity, and technical risk for each potential initiative. Items that pose significant risk to stability, security or scalability are always highest priority. Otherwise, I prefer to prioritize based on end-user impact and moves that will accelerate the product roadmap. This structured, collaborative approach focuses on aligning technical priorities with overall company goals. Of course, priorities can shift rapidly at times, so I stay flexible and re-evaluate as needed when new information emerges.”
6. How do you balance rapid innovation with writing maintainable code?
This tests your ability to deliver innovative solutions while upholding engineering best practices.
Tips:
- Discuss practices like code reviews, refactoring, documentation
- Share how you obtain user feedback to inform iterations
- Provide examples of innovating responsibly
- Highlight how you’ve mentored other engineers
Example: “In order to innovate quickly, it’s critical that engineers don’t compromise on writing clean, well-tested code. I promote best practices like peer code reviews to share knowledge and catch issues early. I allocate time after feature launches to refactor and simplify code while details are fresh. Leveraging design patterns helps strike a balance between rapid prototypes and maintainable implementations. I also mentor junior engineers through code walkthroughs, demonstrating how to uphold standards while moving fast. The result is we can release innovative capabilities frequently while sustaining velocity over the long-term through solid engineering foundations.”
7. Tell me about a time you had to be creative or think outside the box to solve a technical challenge.
This evaluates your problem-solving skills and ability to handle ambiguous technical scenarios.
Tips:
- Share a specific example illustrating the challenge
- Discuss your unique problem-solving approach
- Detail options considered and tradeoffs evaluated
- Emphasize results achieved and impact on the business
Example: “On one project, we needed to develop an image processing algorithm to extract handwritten values from thousands of scanned utility bills to enable automated entry. The complexity of the unstructured data made accuracy extremely difficult. I had the creative idea to utilize deep learning and train a custom convolutional neural network model based on a large sample dataset. This ended up being a breakthrough, allowing us to achieve over 90% accuracy. By thinking outside the box with AI/ML technology rather than relying solely on traditional image processing techniques, we were able to solve a challenge that was previously blocking an important business initiative.”
8. How do you identify technical improvements during development that could enhance the product?
This reveals your product awareness, user-focused mindset and instinct to continuously improve.
Tips:
- Give examples of improvements spotted and suggested
- Discuss soliciting user/stakeholder feedback
- Share process for analyzing data to reveal optimization opportunities
- Show you balance improvements with business priorities
Example: “
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