Data Platform & Analytics
Data Governance & Quality
Named in more postings than SQL. Where an organisation's regulatory exposure physically lives.
Privacy and compliance language appears in 82% of these postings — higher than any tool and higher than SQL. This is not paperwork attached to a data team; it is increasingly the reason the data team exists in the shape it does.
| Time | What you are actually doing |
|---|---|
| 09:00 | An erasure request. Finding every copy of one subject, which is a lineage test wearing a legal costume. |
| 10:30 | Classification at ingestion — tagging columns rather than tables, so everything does not inherit the strictest label. |
| 13:00 | An access review that is about to be rubber-stamped. Reworking it to show unused entitlements rather than all of them. |
| 14:30 | Residency. A replica quietly crossed a border and nobody noticed because nothing checks. |
| 16:00 | Writing the retention schedule that will actually delete things, which requires somebody senior to accept that deletion is safe. |
The decisive round
“How would you know whether our data governance actually works?”
Interviewer: “We have a catalogue, classification and an access review process. How would you assess whether it is real?”
A weak answer. “I'd check that the catalogue is populated, classification is applied across systems, and reviews are completed on schedule.” Measures the existence of controls rather than their operation. All three can be true of a programme that governs nothing.
A strong answer. “I would test operation rather than existence, with four things.
The erasure drill. Pick a synthetic subject and try to find and delete every copy. This exercises inventory, lineage, backups and exports simultaneously, and if it takes more than about an hour the inventory is fiction. I would run it as a drill rather than waiting for a real request.
Revoke rate on access reviews, not completion rate. A campaign closing at 98% completion with a 0.4% revoke rate is a rubber stamp, and completion rate is a vanity metric that rewards exactly that.
Classification granularity. Is it applied at column level or table level? Table-level classification means everything inherits the strictest tag, which means either over-restriction that pushes people into shadow copies, or a tag nobody honours.
A two-user test. Two accounts with different entitlements querying the same asset. If they see the same thing, the access model did not survive whatever pipeline produced that table — and this is where retrieval indexes for AI are currently failing badly.
Then the structural question: is governance a gate people pass through, or a default they get for free? A gate produces shadow pipelines. Classification applied at ingestion, access derived from it, retention scheduled automatically produces compliance nobody had to choose.”
Testing operation rather than existence, and knowing that completion rate and table-level classification are both ways of appearing governed.
- Run an erasure drill on something you control and write down every copy you found and how long it took.
- Build classification-derived access and prove it with two users.
- Convert an access review to exception-based and report the revoke rate.
- Have a retention schedule that actually deletes, and the story of getting someone to accept that.
Compensation
| Market | Band | Notes |
|---|---|---|
| United States | $120k – $210k | Engineering-capable governance sits well above policy-only roles |
| India | ₹12L – ₹40L total | Large BFSI and healthcare GCC demand |
The book for this field
Analytics & BI Tools
The four layers of the analytics stack, then Power BI, Tableau, Looker and Alteryx each in practice — what they are genuinely good at, where they hurt, how to choose with real scenarios, the licensing models that bite, and making analytics actually get used.
Cross-cutting
Skills every archetype tests
These are shared across every field on this site — the same question asked in different vocabulary — so preparation here compounds rather than being spent once. The book above is specific to your field.
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