ROLE
Data engineering
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These are the same questions found in the library, grouped here by the capability each one mainly examines.
453 questions
Questions 51–100 of 453 on this page.
A · Professional problem solving and implementation41
- An order is updated successfully, but a cross-service report reflects it minutes later. The product asks for “real-time status.” How would you define and implement consistency expectations?
- A cross-service flow includes payment, inventory reservation, and shipment. How would you define compensations and irreversible boundaries when later steps fail?
- Incidents recur at service boundaries. Each team can show its service is healthy, but nobody owns end-to-end recovery. How would you repair accountability?
- Several services have separate owning teams, yet a small change often requires three or four teams to release together. How would you assess whether the service boundaries have failed?
- After code changes, the build system sometimes misses affected apps and sometimes rebuilds the entire repository. How would you validate the dependency graph and cache invalidation rules?
- One repository contains multiple teams and production deployment config, but code-owner rules do not cover temporary admins and automation accounts. How would you review permission and approval boundaries?
- Two product packages form a dependency cycle, and splitting them creates a need to share domain types. How would you change the boundaries without hiding the cycle in a new shared package?
- A team decides to split a large repository, but history, CI, package releases, and ownership are connected. How would you sequence the migration?
- In a monorepo, shared packages are casually changed by one team, while consumers discover behavior changes only after upgrading. How would you establish ownership and compatibility contracts?
- Packages have very different release cadences, but shared version numbers force unrelated teams to release together. How would you design versioning and release policy?
- The repository has hundreds of packages and full CI is slow. The team wants to test only “affected” areas. How would you prove selective testing does not miss critical dependencies?
- A user requests deletion of personal data, but some records have reached backups, analytics warehouses, and downstream systems. How would you design a verifiable deletion process?
- A widely used dependency is disclosed as critically vulnerable, but upgrading may introduce compatibility issues. How would you sequence the response?
- Service failures have exceeded the target range, but the business has firm feature commitments. How would you adjust the release pace and investment in reliability?
- Backups report success, but the team has never verified restored data integrity or recovery time. How would you establish demonstrable recovery capability?
- A new external service will access user data and trigger internal actions. How would you perform a lightweight but effective threat model?
- The system uses pre-signed URLs for private downloads, but links can be forwarded or retained for a long time. How would you design authorization and expiry boundaries?
- How should the permission system of a large operations back office be designed? How do you organize roles, data scope, approvals, and audit, and how do you keep it from getting out of control as permissions multiply?
- Issuing a coupon after payment used to run synchronously, and it is being changed to an async queue with retries. Review this change: which failure sequences worry you most, and what would you rehearse before release?
- How would you design a platform where operations staff build campaigns and game mechanics themselves? How do you abstract campaigns, mechanics, rules, and features into configurable parts, and how do you keep a configuration correct once it goes live?
- Before drawing any architecture diagram, which few numbers would you use to decide whether a service should be split or cached? Use a service you know to explain.
- From an engineering view, how do you estimate the overall cost of a system? How are storage and compute costs each calculated, and which grow linearly with scale and which do not?
- When the business operates across several countries and regions and user data must flow across borders, how do you solve data compliance in systems and processes, and how do you judge and decide in gray areas where the rules are unclear?
- The local database has updated, but syncing the cache or sending a downstream message fails. How would you make the systems converge and handle retries, compensation, or manual recovery?
- A major promotion or international launch may increase traffic fivefold next year. Starting from the current architecture, how would you check for bottlenecks in the gateway, critical request flows, storage, and machine resources? How would you phase the work, staff it, and validate your assumptions?
- Design a collaboration product that supports large-file uploads with resumability, where files must be validated and scanned before other members can access them. What constraints would you clarify, and how would you design upload, temporary storage, scanning, publication, permissions, and cleanup boundaries?
- How would you design a large-model chat system? How do you handle streamed output, multi-turn context, history, interruption, and retries, and how do you control cost and latency?
- How do the costs of a recommender system add up, including retrieval, ranking, feature serving, storage, and experimentation? How would you trade effect against cost?
- How would you design an invitation-based viral marketing campaign? How do you design invitation relationships, reward payout, abuse prevention, and effect evaluation?
- How would you design a real-time risk control system? How do rules, features, models, and manual review work together, and how do you trade false blocks against misses?
- How would you design a search system? How do indexing, retrieval, and ranking divide the work, how are Chinese segmentation and features built, and how do you judge how good the search is?
- Tell me about a project you worked on. Why did you choose that technical approach over the others, how was the decision made, and what were its pros and cons?
- How should coupons, discounts, and flash sales integrate with a trading system without slowing the core transaction flow? How would you calculate, combine, and reconcile discounts?
- Public benchmarks keep improving while internal task performance stalls. How would you investigate evaluation distortion?
- After AI output causes actual user harm, product, model, operations, and review teams all take part in the response. How would you divide incident handling and follow-up improvement?
- After replacing a foundation model, overall metrics remain similar but some users report worse results. How would you identify what changed in model behavior and decide whether to roll back?
- You need to sample production AI conversations for emerging risks, but they contain personal or commercial data. How would you design the review?
- A third-party model provider changes its training, retention, or cross-border terms. When should calls pause or receive renewed approval?
- Average AI quality meets the target, but a few high-risk errors can cause harm. How would you set the release gate?
- An AI assistant can call internal tools, but tasks require different permissions. How would you design authorization and audit?
- Overall AI accuracy passes, but one language or user segment has a higher error rate. How would you assess and respond?
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B · Business understanding and domain modeling5
- Renewal fell by six percentage points this quarter, while the share of small customers among new accounts rose. How would you segment customers, usage periods, and service cost to determine whether product value fell or the customer mix changed?
- Sales reports growth using signed contract value, but customers will not use the product for months. How would you distinguish contracting, fulfillment, revenue recognition, and customer value, and explain what the team should observe?
- A premium service tier earns more revenue but consumes more human support, and renewal has not improved. How would you determine whether it creates incremental value?
- A product is sold once but requires long-term support and upgrades. Revenue is growing while the service queue accumulates. How would you decide whether these sales still create value?
- A customer buys a bundle and then asks to refund one item. How should the original bundle discount be reallocated?
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C · Value judgment and direction setting4
- Visits and registrations are growing, but match success is falling. Demand concentrates in a few regions while suppliers are scattered. How would you find the liquidity bottleneck and choose where to invest first?
- A marketplace raises commission by two points. Revenue rises short term, but some high-quality suppliers list less often; buyer conversion has not moved yet. How would you assess long-term impact?
- After a subscription price increase, monthly revenue rises 8%, but cancellations grow among small core customers. Sales wants to continue. How would you estimate net benefit and long-term risk?
- Gross margin is steady, but standard-service revenue falls while custom-service revenue grows, along with implementation and support hours. How would you determine whether growth is healthy?
No questions in this section match your target. ·