Scale Engineer

Senior Director

Software Engineering ManagerM6Very High

The interview process for a Senior Director Software Engineering Manager (M6 level) at Databricks is a rigorous and multi-faceted evaluation designed to assess leadership capabilities, technical depth, strategic thinking, and cultural fit. Candidates are expected to demonstrate a strong track record of building and scaling high-performing engineering teams, driving complex technical initiatives, and contributing to the overall product vision and business strategy.

Rounds·5

Timeline·~30d

Experience·10 - 15 yrs

Comp band·US$250000 - US$350000

Interview time·270 min

Evaluation

What they measure.

  • Technical Acumen: Depth of understanding in relevant technologies, ability to guide technical decisions.
  • Leadership & People Management: Ability to inspire, mentor, and develop engineers; experience in performance management and team building.
  • Strategic Thinking: Vision for product development, ability to align engineering efforts with business goals.
  • Execution & Delivery: Track record of successfully delivering complex projects on time and with high quality.
  • Communication & Collaboration: Clarity in communication, ability to influence stakeholders, and foster cross-functional partnerships.
  • Cultural Fit: Alignment with Databricks' values, including collaboration, innovation, and customer focus.

Preparation

How to prepare.

Tips

  1. Deeply understand Databricks' mission, values, and product offerings.
  2. Review your past projects and identify key achievements and learnings relevant to leadership and technical execution.
  3. Prepare specific examples using the STAR method (Situation, Task, Action, Result) for common leadership and behavioral questions.
  4. Familiarize yourself with distributed systems concepts, cloud computing, and data engineering principles.
  5. Research current trends in the data and AI industry.
  6. Practice articulating your leadership philosophy and management style.
  7. Understand Databricks' organizational structure and how engineering teams contribute to its success.
  8. Be prepared to discuss your approach to hiring, onboarding, and retaining top engineering talent.
  9. Think about how you would handle common challenges faced by engineering managers, such as technical debt, team conflicts, and resource constraints.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Company and Self-Assessment

Weeks 1-2: Databricks company overview, product knowledge, and self-reflection on career achievements.

Weeks 1-2: Deep dive into Databricks. Understand the company's history, mission, values, product suite (Lakehouse Platform, MLflow, Delta Lake, Spark), and competitive landscape. Review recent company news and investor relations materials. Focus on understanding the strategic importance of engineering in Databricks' success. Begin reviewing your career history to identify key leadership and technical accomplishments.

Questions

Commonly asked.

  • Describe your experience in building and scaling engineering teams from X to Y engineers.
  • How do you foster a culture of innovation and accountability within your team?
  • Tell me about a time you had to make a difficult technical decision that impacted multiple teams. What was the outcome?
  • How do you balance technical debt with new feature development?
  • Describe your approach to performance management and career development for your engineers.
  • How do you handle conflict within your team or with other departments?
  • What is your strategy for attracting and retaining top engineering talent?
  • Tell me about a time you failed. What did you learn from it?
  • How do you stay current with emerging technologies and industry trends?
  • Describe a complex project you led from conception to delivery. What were the key challenges and how did you overcome them?
  • How do you ensure alignment between engineering efforts and business objectives?
  • What are your thoughts on the future of data engineering and AI, and how would you position Databricks for success?
  • How do you delegate tasks effectively and empower your team members?
  • Describe a time you had to influence stakeholders without direct authority.
  • What are the key metrics you use to measure the success of your engineering team and projects?

Locations

Regional differences.

Fig · Regions — 03 locations

01 / 03

Location

San Francisco Bay Area

Interview focus

Adaptability to different work environments (remote, hybrid, in-office).Experience with managing distributed teams and fostering collaboration across different time zones.Understanding of the local tech talent market and competitive landscape.

Common questions

  • How do you handle underperforming teams in a remote setting?
  • Describe a time you had to adapt your leadership style for a geographically distributed team.
  • What are the unique challenges and opportunities of managing engineering teams in the Bay Area versus other tech hubs?

Tips

  • Highlight experience with remote team management tools and strategies.
  • Be prepared to discuss your approach to building culture in a distributed environment.
  • Research Databricks' presence and engineering culture in the specific location.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

DSA

Coding questions at Databricks.

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