1. Feature Freshness advanced

    How should feature freshness requirements be decided, and what does getting them wrong cost?

    2 min answer feature-freshnesslatencycostskew
  2. File Formats & Compaction advanced

    A lakehouse table takes 400 GB a day from a streaming job that commits every 60 seconds across 24 partitions. Daily compaction rewrites yesterday's data and a weekly job re-sorts the last 30 days. Roughly how much compute does that maintenance need, what share of the bill is it, and which assumption dominates the error?

    3 min answer compactionmaintenanceplanning-numberscost
  3. File Formats & Compaction intermediate

    A lakehouse team raises its compaction target file size from 128 MB to 1 GB and switches the write codec from Snappy to Zstandard. Query cost falls. What did they give up, and when does that bill arrive?

    2 min answer datadogcompactionparquetzstd
  4. File Formats & Compaction intermediate

    A platform's analytical queries slow steadily over months with no change in data volume per day. What is happening?

    2 min answer small-filescompactionformatsmetadata
  5. File Formats & Compaction intermediate

    A table written by a streaming job has become unusably slow. It holds 400 GB across 8 million files. Diagnose and fix.

    2 min answer performancecompactionstreaming
  6. File Formats & Compaction beginner Multiple choice

    A team keeps three years of event data as gzipped CSV in object storage because it is simple and anything can read it. The table is now about 500 GB compressed and the daily dashboard query reads four of the 60 columns. What has the simplicity actually cost them?

    2 min answer csvparquetgzipsplittability
  7. File Formats & Compaction advanced

    Review this configuration. A 60 TB events table is partitioned by ingest_date and written by a streaming job that commits every 60 seconds. A compaction job runs hourly over the last 24 hours with a 512 MB target and sorts each file by event_timestamp. Snapshot expiry runs monthly with 90-day retention. 85% of queries filter on customer_id over a 7-day range. What would you remove, what would you change and what would you leave alone?

    3 min answer compactionsort keysnapshot expirystatistics
  8. Financial Services Regulation advanced

    A national payments rail routes billions of transactions across banks of varying reliability, and a bank switch times out after debiting but before confirming. How should timeouts, deemed status, reconciliation, reversals and customer messaging be designed so money is never lost or double-spent?

    3 min answer upinpcireconciliationdeemed-success
  9. Financial Services Regulation advanced

    A payments institution must satisfy prudential and conduct regulation. Which architectural properties do these requirements actually demand?

    2 min answer phoneperegulationauditsegregation
  10. Financial Services Regulation advanced

    An exit plan requirement must be credible and tested. What does that mean for how you build?

    2 min answer exit-planportabilitylock-inregulation
  11. Financial Services Regulation advanced

    Interview. A regulator asks you to demonstrate that a specific customer payment processed on 14 March could not have been handled outside the UK. Walk me through what you would show, and what you would have had to build beforehand.

    3 min answer regulatory-evidencedata-residencycontrol-evidenceaudit
  12. Financial Services Regulation advanced

    What does financial services regulation demand of architecture that a general-purpose system does not provide?

    1 min answer financial-servicesauditresiliencereporting