FDE Times: Nishant Bhajaria’s Data Privacy — a runbook for classification, deletion and DSAR export before handover
A 5 November FDE Times review of Manning’s 384-page 2022 book (author led privacy engineering at Uber, Netflix and Google) says FDEs should treat it as a stage-by-stage runbook: label columns by risk in week one, bring a one-page privacy review template before first ship, then hand over deletion/export flows built from a user_id catalogue.
At handover, clients ask who can see which column, how deletion and export work, and where consent lives — and a stalled legal review can kill a working demo. FDE Times’s 5 November review of Nishant Bhajaria’s Data Privacy: A runbook for engineers (Manning, 2022, 384 pages) argues the book is most useful consulted by engagement stage, not cover to cover.
Bhajaria led technical privacy work at Uber, Netflix and Google. The table of contents follows a real programme: classify and inventory first, then build review, deletion, DSAR export and consent tooling, and leave org/regulation for last. A free-text “notes” field that looks harmless can hold names and addresses and must be labelled high risk before it enters a feature store.
Practical FDE takeaways: send a risk-labelled column table to the client’s data owner in week one; bring a one-page privacy-review template (what data, why, who, retention) so legal checks instead of investigates; and build a catalogue of which tables hold user_id so export and deletion are features you hand over, not scripts written under pressure. Data you never pull in is data you never have to protect.
Source: fdetimes.net