These questions are based on real interview experiences from candidates who interviewed at this company. You can practice answering them interactively on Dataford to better prepare for your interview.

Approach your preparation as you would a complex delivery: define the scope, build a plan, practice under realistic constraints, and test your communication. The process evaluates both how you think and how you lead. Depth in system design, crisp storytelling with data, and values alignment will differentiate you.

• Role-related knowledge – Interviewers look for fluency in distributed systems, API/platform design, data modeling, and reliability engineering as relevant to Atlassian’s SaaS products. Demonstrate practical judgment in architecture, trade-offs across consistency, latency, cost, and operability. Show currency with modern cloud patterns, not just textbook designs.

• Problem-solving ability – You will be evaluated on structured thinking under changing requirements. Strong candidates clarify constraints, reason from user needs, iterate designs, and quantify trade-offs. Narrate your approach, not just the end state.

• Leadership – Expect to discuss how you set direction, develop talent, manage performance, and influence without authority. Interviewers will probe your mechanisms for execution (cadence, KPIs/OKRs, risk management) and how you coach senior ICs.

• Culture fit / values – Atlassian prizes openness, customer focus, teamwork, and proactive change. Interviewers look for how you communicate transparently, handle conflict, and make decisions that “don’t #@!% the customer.” Use STAR stories to show your behaviors, not just intentions.

For the Engineering Manager role, you will experience a structured but conversational loop focused on system design, people leadership, strategic execution, coding/code design, and values. Reports from online interview communities indicate a technical-first approach: the first live conversation is often a system design or technical phone/video screen. Subsequent stages combine behavioral deep dives with scenario-based strategy discussions, culminating in a values interview.

Expect rigor and dynamism. Interviewers commonly add evolving requirements during design to assess adaptability and prioritization. Coding appears as a live exercise or a code-design/LLD round suited to managers who still reason about code quality, APIs, and complexity. The process emphasizes collaboration, clear articulation of trade-offs, and customer-minded decisions rather than trick questions.

Compared with many companies, Atlassian leans into practical, product-grounded discussion. You will be expected to tie architecture to business outcomes, connect execution mechanisms to measurable impact, and reflect the company’s values in how you communicate and decide under ambiguity.

This visual shows the typical progression from recruiter screen to technical/system design, people management and strategic execution, coding/code design, and a values interview. Use it to plan time-bound prep sprints for each cluster (design, leadership, coding, values), and to manage energy across a multi-stage loop. Timelines and emphasis vary by team, location, and level (e.g., Senior EM), but the same core themes recur.

System Design and Architecture

This area matters because Atlassian EMs guide architectural direction while balancing velocity and reliability. You will design systems that could plausibly exist inside Atlassian’s product suite (e.g., content tools, tagging, feeds, indexing/crawling). Strong performance means clarifying requirements, proposing sensible end-to-end designs, evolving them as constraints change, and quantifying trade-offs.

Be ready to go over:

• Content and collaboration primitives – Designing a Color Picker Tool or hierarchical content storage that scales across tenants, includes real-time collaboration, and supports accessibility and i18n.
• Metadata and taxonomy – Tag management systems for discoverability, permissions-aware filtering, and multi-dimensional search with indexing strategies.
• Content feeds and ranking – Popular feed design: aggregation, ranking signals, caching, and backfill; controlling fan-out/fan-in and cost.
• Advanced concepts (less common) – Multi-region data residency, GDPR/DSR, eventual vs. strong consistency, saga/outbox patterns, idempotency, rate limiting, circuit breaking, backpressure, and observability strategies (SLIs/SLOs).

Example questions or scenarios:

• “Design a Color Picker Tool for Confluence that supports theming, accessibility, and plugin extensibility. How do you version palettes and roll out changes?”
• “Build a Tag management system for documents with permissions-aware search. How would you model tags and keep the index consistent?”
• “Design a popular content feed for Confluence. Discuss ranking, caching, and backfill. What happens during spikes?”
• “Sketch a web crawler for internal documentation. How do you avoid over-crawling, dedupe content, and handle robots/permissions?”
• “Design a hierarchical data storage system that supports move/rename operations at scale without breaking links.”

People Management

You will be assessed on how you grow people, manage performance, and build healthy teams. Interviewers look for specific mechanisms: career frameworks, feedback loops, hiring calibration, and how you intervene early on delivery and interpersonal risk. Strong performance pairs empathy with clarity—clear expectations, timely feedback, and measurable growth.

Be ready to go over:

• Coaching and leveling – How you set growth plans, calibrate expectations, and mentor senior ICs vs. junior engineers.
• Performance management – Addressing underperformance, conducting difficult conversations, and documenting action plans.
• Team health and communication – Psychological safety, conflict resolution, and rituals that amplify signal (1:1s, retros, demo days).
• Advanced concepts (less common) – Building a hiring bar-raiser loop, org design during growth/mergers, and succession planning.

Example questions or scenarios:

• “A senior engineer resists architectural direction. How do you align without eroding autonomy?”
• “Two high performers are in conflict, impacting delivery. Walk us through your intervention.”
• “Describe a time you raised the hiring bar. What changed in your process and outcomes?”
• “How do you approach performance improvement when signals are ambiguous?”

Strategic Execution

This area evaluates how you translate strategy into results—prioritization, sequencing, risks, and cross-functional alignment. Interviewers will probe how you create clarity from ambiguity, set measurable goals, and adjust plans when constraints or inputs change. Strong candidates show repeatable execution systems and data-driven trade-offs.

Be ready to go over:

• Prioritization frameworks – How you combine user value, effort, risk, and strategic bets; managing tech debt and platform investments alongside features.
• Operating cadence – OKRs, release planning, burndowns/burnups, and incident/defect SLAs; how you course-correct mid-quarter.
• Change management – Communicating pivots, preserving morale, and renegotiating scope or timelines with partners.
• Advanced concepts (less common) – Portfolio-level capacity planning, build-versus-buy for platform components, cost-to-serve modeling.

Example questions or scenarios:

• “Mid-quarter, product changes priorities. How do you re-sequence work without burning the team?”
• “You inherit a roadmap heavy on features, light on reliability. How do you rebalance?”
• “Describe a time you managed a cross-team dependency that was blocking your critical path.”

Coding and Code Design (LLD)

EMs at Atlassian are expected to reason about code quality and design, even if not writing production code daily. You may face a live coding exercise or a code design/LLD discussion. Strong performance means writing clear, tested code in a familiar language or articulating class/API design with attention to complexity, edge cases, and maintainability.

Be ready to go over:

• Live problem solving – Implementing data structures or parsing tasks; walking through test cases and trade-offs.
• LLD/API design – Designing services, classes, and interfaces; separation of concerns, dependency management, and error handling.
• Quality and testing – Unit tests, input validation, and observability hooks.
• Advanced concepts (less common) – Concurrency control, back-of-the-envelope complexity/cost estimates, and API evolution/versioning.

Example questions or scenarios:

• “Design an API for a Tag management service. How would you handle duplicates, renames, and eventual consistency?”
• “Implement a function to flatten a hierarchical data structure while preserving parent relationships.”
• “Walk through how you would test and instrument a ranking component for a popular feed.”

Values and Collaboration

The values interview tests how you work: openness, customer obsession, teamwork, and proactive change. Expect prompts to evidence how you communicate transparently, make customer-first decisions, and improve systems. Strong performance is story-driven, specific, and reflective of outcomes and learnings.

Be ready to go over:

• Open communication – Sharing context, writing design docs, and receiving feedback with humility.
• Customer-first choices – Handling incidents, rollback decisions, and quality bars.
• Team play – Cross-functional wins, credit sharing, and how you build trust.
• Advanced concepts (less common) – Ethical decision-making amidst pressure, investing in docs/tech debt against short-term targets.

Example questions or scenarios:

• “Tell us about a time you disagreed with product but aligned on a customer-first decision.”
• “Describe a failure you owned publicly. What changed afterward?”
• “When did you proactively fix a broken process without being asked?”

This word cloud highlights frequent themes reported by candidates, such as system design topics (tagging, feeds, crawlers, hierarchical storage), people leadership, strategic execution, coding/LLD, and values alignment. Larger terms appear more often and signal higher prep ROI. Prioritize depth in the biggest clusters, then differentiate with advanced topics relevant to your target team.