This is a fully remote Data Visualization Specialist position paying up to $88,000 a year, open to candidates anywhere. The role sits on a small analytics team that turns raw business data into visuals people can actually act on.
What you'll be doing
The job is built around one core skill: taking messy, complex datasets and turning them into something a non-technical stakeholder can look at and immediately understand. That means building dashboards, cleaning up how metrics are displayed, and sitting in on conversations with analysts to figure out which numbers actually matter for a given decision. You'll spend a good chunk of your time going back and forth on a chart until it says what it's supposed to say without a paragraph of explanation next to it.
- Transform complex datasets into clear, interactive visuals and dashboards
- Work directly with analysts and business stakeholders to define which metrics belong front and center
- Revise and refine existing visuals, so they hold up under real scrutiny, not just at first glance
A lot of the day-to-day is iterative. A dashboard that looked clean in a design review often needs another pass once real users start clicking around in it, and part of the job is being fine with that instead of treating the first version as final. Stakeholders will sometimes ask for a chart type that doesn't actually fit the underlying data, and pushing back on that respectfully, with an alternative in hand, is a normal part of the work rather than a rare exception.
What you'll need
A bachelor's degree is the baseline requirement here — the source data doesn't specify a narrower field, so data science, design, statistics, or a closely related discipline should all be reasonable fits, provided the coursework or portfolio backs up genuine visualization ability. Naukri Mitra has seen candidates from unconventional academic paths succeed in this role as long as the portfolio does the talking.
In terms of experience, the requirement is 24 months in a visualization or closely related analytics role. A portfolio matters more than a job title here; hiring managers want to see dashboards or visual work built for actual business or research audiences, not just coursework exercises.
- Tableau
- Power BI
- D3.js
- Data storytelling
- Design principles
- SQL
- Statistics
Comfort with SQL is non-negotiable, since most of the source data you'll pull from lives in relational databases before it ever reaches a dashboard tool. Design principles matter just as much as the software itself; knowing how to build a chart in Tableau is different from knowing when a bar chart is the wrong choice entirely. Statistical knowledge doesn't need to be advanced, but you should be able to spot when a trend line is misleading or when a sample is too small to support the story a chart tells. That kind of judgment is what separates a technically correct visualization from one that actually earns trust from the people reading it.
Nice to have
None of the following are dealbreakers, but they'll strengthen an application. Familiarity with Python for data wrangling before visualization work is useful when the raw data requires more cleanup than a spreadsheet tool can handle. Experience with a cloud data warehouse like Snowflake or BigQuery helps if the team's pipelines eventually move that direction. Some exposure to Figma or another design tool is a plus for anyone who wants more say in a dashboard's visual language beyond what a BI tool defaults to. Any prior work presenting findings to non-technical audiences, whether to a client, an executive team, or a research committee, translates well to this role, since the actual craft of the job relies as much on communication as on the tooling.
Pay and benefits
This is a full-time, remote position with an annual salary around $88,000 USD. Full-time visualization roles at this level typically come with a fairly standard benefits package, and this one is no exception.
- Health insurance
- Paid time off
- 401(k) matching
- Remote-work flexibility, with the freedom to work from anywhere
- Wellness stipend and a home-office equipment allowance for remote staff
$88,000 sits solidly within what's typical for a mid-level remote data visualization specialist role, though pay for these positions varies by industry and by how specialized the required tool stack is. Most people who reach this level did a few years building dashboards inside a broader analytics or BI team first, then moved into a role this dedicated once their portfolio was strong enough to stand on its own.
Team and day-to-day rhythm
Because the role is fully remote and the team is small, much of the collaboration happens asynchronously through shared documents and recorded walkthroughs rather than back-to-back meetings. That suits people who like to think through a visualization problem on their own time before presenting it, but it does mean you need to be comfortable writing clearly about your work, since not every decision gets explained live in a meeting. Deadlines cluster around reporting cycles, so some weeks are quieter than others and some weeks have several dashboards due at once. Since the team is distributed across time zones by design, working from anywhere is genuinely built into how this role operates rather than a perk bolted on afterward, and overlap hours for live discussion tend to be limited to a couple of hours a day.
How to apply
Candidates who meet the education and experience requirements above should apply with a resume and a portfolio link that shows at least two or three visualization projects, ideally accompanied by a short note on the business question each one answered. Applications without a portfolio are unlikely to move forward, since that's the clearest signal of whether someone can do this specific job well. Given the remote and global nature of the role, expect the first interview to be scheduled across time zones with some flexibility on both sides.
This posting is open to applicants anywhere, and the hiring team has reviewed candidates from a wide range of countries for similar data visualization specialist jobs in the past, so there's no location restriction beyond the ability to work the limited overlap hours mentioned above. Shortlisted candidates should expect a short take-home exercise built around a small dataset, followed by a walkthrough call where you talk through the design choices you made rather than just the finished chart. That second part tends to matter more than the exercise itself, since it's the closest thing to watching how someone actually thinks through a visualization problem in real time.
