Why pre-screen data visualisation developers before the technical interview
Most dashboards are built to display what is available rather than to answer a question, and they are abandoned within months. Developers who avoid that start from the decision the viewer has to make, remove anything that does not serve it, and check whether people still open it. The other constraint is volume: a visualisation that renders instantly on sample data can be unusable on the real thing. A short screen tests both.
What actually matters when screening Data Visualisation Developer candidates
- 01
Technical proficiency
Check fluency in D3.js, Observable Plot or Vega-Lite plus the surrounding stack: React or Svelte, SVG and Canvas rendering, SQL against the warehouse, Tableau or Power BI extensions.
- 02
Systems and trade-offs
Probe how they handle scale: rendering 500k points without freezing the browser, aggregation server side versus client side, WebGL fallbacks, caching, incremental loading in dashboards.
- 03
Evidence and rigour
Assess how they validate that a chart tells the truth: axis truncation, colour scales tested for colour blindness, WCAG contrast, accessible tables, usability testing with real analysts.
- 04
Collaboration and communication
Look for work with analysts, product managers and non-technical stakeholders: turning vague requests into specs, running design reviews, documenting a shared chart component library.
Pre-screening questions to ask Data Visualisation Developer candidates
12 questions grouped by what they test. Ask the same set in every screen and score answers on a consistent scale, or send them as an async video screen and compare answers side by side.
Work people use
3 questions01What are some of the major projects that have featured your visualisation work?
Listen forWork still in use with a sense of how many people open it, and the decision each piece supports.
Projects described by appearance, or no idea whether anything is still being used.
02What platforms have you worked on, and what makes you comfortable with them?
Listen forPlatforms chosen for the audience and the data, with an honest view of where each falls down.
One platform used for everything, or tools named with no critical view.
03What are your technical proficiencies with regard to visualisation tools?
Listen forBoth a business intelligence tool and custom development capability, with a view on when each is appropriate.
Custom development proposed for problems a reporting tool solves, or the reverse.
Charts that answer
3 questions04What do you consider the most important aspect of a good visualisation?
Listen forThe question being answered placed first, with a view that anything not serving it should be removed.
Aesthetics or interactivity named first, or an answer about making data engaging.
05How do you translate complex data into a format non-technical people understand?
Listen forChart types chosen for the comparison being made, with an example of simplifying without misleading.
Complexity handled by adding explanation, or chart types chosen for visual variety.
06How do you give users the ability to explore a visualisation in more detail?
Listen forDrill-down designed around questions people actually ask next, rather than exposing every dimension.
Every field made filterable, or interactivity added with no view on what users would do with it.
Performance at volume
3 questions07How do you handle large amounts of data in your visualisations?
Listen forAggregation pushed to the database with rendering limits understood, and a performance problem they solved.
Full datasets sent to the browser, or performance tested only on sample data.
08Have you worked with real-time data visualisation?
Listen forUpdate frequency matched to what viewers can act on, with the load cost of frequent refresh understood.
Real-time updates applied where nobody acts that quickly, or refresh rates set with no cost consideration.
09How do you ensure the accuracy of data in your visualisations?
Listen forTotals reconciled against a trusted source, with a case where a chart was wrong and how it was caught.
Accuracy assumed because the query ran, or no reconciliation against an independent figure.
Numbers checked
3 questions10How would you handle design feedback and criticism of your work?
Listen forFeedback tested against whether the visualisation answers the question, rather than accepted or rejected on taste.
Every request implemented, or feedback dismissed as a lack of data literacy.
11Can you describe your process for testing visualisations and fixing issues?
Listen forTesting with edge cases such as missing data, single categories and extreme values, plus real users.
Testing with clean sample data only, or no check of what happens when a series is empty.
12Do you have experience collaborating with data or analytics teams?
Listen forWorking relationships with analysts, with a case where they pushed back on a chart that would mislead.
Requirements taken and built literally, or no occasion where they challenged a requested chart.
How to score responses
Score every candidate on the same four criteria immediately after the screen. At this stage you are shortlisting for panel interviews, not making the final call.
Technical proficiency
35%5Names specific chart implementations built from scratch in D3 or Canvas, explains scales, axes, transitions and data joins without hesitation.
Systems and trade-offs
25%5Cites concrete performance numbers and the trade-off chosen, for example switching SVG to Canvas or pre-aggregating in DuckDB to cut load time.
Evidence and rigour
25%5Describes rejecting or reworking a visual because it misled readers, and cites accessibility checks or user testing that drove the change.
Collaboration and communication
15%5Shows a repeatable intake process, gives examples of reframing a stakeholder's chart request into the question actually worth answering.
Most dashboards display what is available rather than answer a question, and get abandoned. A one-way video screen asks what they removed.
Try it on HirevireScreening FAQ
Process basics
How long should a pre-screening round for this role take?
Fifteen minutes across eight to ten questions, answered async, with links to work. Enough to establish what is still in use, test their chart reasoning, and hear how they handle data volume.
Should I screen for design or engineering?
Both, and candidates lean one way. A designer-leaning developer makes clear charts that may not scale; an engineer-leaning one builds fast dashboards that mislead. Decide which risk matters more to you.
Evaluating answers
What is the strongest signal when screening this role?
Something they removed. Developers who think about the viewer cut charts that nobody used or that misled. Anyone whose dashboards only grew has been adding whatever was requested.
How do I judge whether their work is used?
Ask how many people open it weekly. Developers who care about impact know, because usage is measurable. Anyone who only knows what was delivered has not followed up after handover.
Go deeper on this role
Sanat has been hiring since 2012 and watching the recruitment industry change up close ever since, and turned that screening process into Hirevire's video screening platform. LinkedIn
