What is a data warehouse vs. a transactional database?
Tests your grasp of read-optimized (OLAP) vs. write-optimized (OLTP) systems. A great answer defines warehouses for analysis, contrasts them with transactional DBs for operations, and explains the resulting differences in workload, schema, and data structure.
ETL vs. ELT: Key differences and when to use each?
This tests your understanding of modern data architecture trade-offs. A good answer explains the T vs. L order, then links ETL to structured, legacy systems and ELT to flexible, cloud-native data lakes/warehouses.
Guarantee at-least-once delivery for a critical event?
This tests your grasp of atomicity without 2PC. A great answer outlines the Transactional Outbox pattern: write the event to a DB table in the same transaction as the business logic, then use a relay process. A red flag is relying on simple try/catch blocks.
Design a client-side event batching system for a high-traffic app
This tests your grasp of frontend performance and data reliability. Outline a batching strategy (timer/size), then explain using `visibilitychange` with `navigator.sendBeacon()` to prevent data loss on unload. A red flag is suggesting synchronous XHR.
Build vs. Buy: Third-Party vs. In-House Analytics
Tests your grasp of the time-vs-control trade-off. A great answer weighs speed vs. customization and total cost of ownership. Advocating for 'build' without considering the massive, ongoing maintenance cost is a major red flag.
How would you debug a sudden drop in a key metric?
Tests your systematic debugging of complex data systems. First, validate the drop against a source of truth and segment the data. Then, hypothesize causes like misattribution or data loss.
How do you track page views in a Single Page Application?
This tests your grasp of SPA routing mechanics. A great answer covers both programmatic navigation (using router hooks) and browser history events (`popstate`), explaining why both are necessary.
Explain the North Star Metric and propose one for a product
Tests your ability to link product strategy to a single metric reflecting customer value and business growth. Define the NSM, propose one for a product like Spotify, and justify it. A red flag is picking a vanity metric like DAU or a pure business metric.
How would you diagnose a flat feature adoption KPI?
This tests your ability to create a diagnostic plan from a single lagging metric. A great answer outlines a funnel (Awareness > Activation > Usage), segments users, and combines quantitative data with qualitative feedback.
Translate 'increase engagement' into a technical measurement plan
This tests your ability to translate vague business goals into concrete metrics. First, clarify the goal with the PM. Then, propose specific, measurable proxy metrics (e.g., DAU/MAU, session length). Finally, outline the instrumentation plan.
ETL: The Assembly Line for Your Data
ETL (Extract, Transform, Load) is an assembly line for data, moving it from various sources into a single destination for analysis. It's used to populate data warehouses by combining data from databases, logs, and APIs into a unified view.
Study: Disclosing AI use makes you seem 10x lazier
A study of ~1,000 workers found disclosing AI use makes you seem 10x lazier. Even with identical output, peers were 24% less likely to recommend you for key projects. While 94% use AI, the stigma means silence is often the safest career strategy.
Atlassian Details its ML Studio Platform Design
Atlassian's ML Studio platform powers thousands of daily workflows for millions of Rovo users. It solves enterprise scaling issues with reusable modules, column-level data governance, and unified orchestration, offering a blueprint for building compliant…
How do you build a business case for technical debt work?
Tests your ability to translate technical issues into business impact. Frame debt as business risk, quantify its impact on velocity and cost, and propose a clear, capacity-based plan.
Distinguish Throughput from Velocity in agile planning
This tests your grasp of outcome (Throughput) vs. effort (Velocity) metrics. Define both: Throughput is item count/time, Velocity is points/sprint. Contrast them by explaining Throughput measures actual delivery, not estimates.
Coaching a team from dependency to self-management
This tests your ability to apply a maturity model (like Tuckman's) to Agile coaching. Outline your shift from directive teaching in Forming to challenging in Performing, retiring basic facilitation as the team matures. A red flag is a static coaching style.
How would you advocate for decentralizing deployment approvals?
This tests your ability to drive organizational change with data. A great answer frames the problem using a decision framework (e.g., SAFe), proposes a phased pilot, and defines metrics like Cycle Time and Change Failure Rate to prove value.
A manager wants to attend your team's Sprint Retrospective. What's the risk?
Tests your grasp of psychological safety in Agile and stakeholder management. A great answer identifies the risk of chilled feedback, diagnoses the manager's underlying need, and proposes an alternative forum.
How would you design an architecture for rapid product iteration?
Tests your grasp of evolutionary architecture for uncertain markets. A great answer outlines incremental change via modularity and CI/CD, fitness functions to guard qualities like security, and evolving across multiple dimensions (tech, data).
How do you quantify the cost of not addressing technical debt?
Tests your ability to translate technical issues into business impact. A good answer quantifies the slowdown, calculates the 'tax' on new features, and proposes a specific, time-boxed plan. A red flag is complaining about the PO without providing data.