Data Visualization Engineer
Tempus AI · Chicago · US
Software Engineering
–
Not yet analysed
Demand62
Career growth58
Healthcare fit32
Remote potential55
5-year outlook
Data visualization and analytics engineering skills remain in steady demand across health tech, and precision-medicine companies tend to pay competitively within the broader tech market. Exact figures cannot be estimated from this posting, and growth depends heavily on whether the role stays IC-focused or expands into data platform leadership.
Clinical license
Not required
Applicant reach
narrow
Seniority
unclear
Employment type
–
Date found
2026-10-07
Intelligence details
Flexible work details
- Eligible countries
- United States
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Worth considering only if you already have genuine software or data-visualization engineering experience alongside your clinical background — this is not a typical clinician transition role. Clinicians without coding/BI portfolios are unlikely to clear the technical bar.
Who should apply
Clinician-engineers and clinical informatics professionals with hands-on dashboarding or front-end development experience; healthcare graduates with a computer science or data analytics degree; physician-scientists or research staff who have built visualization tooling for clinical or genomic datasets.
CV angle
Lead with any real technical delivery: dashboards, registries, or analytics tools you built or specified, naming the stack (SQL, Python/R, Tableau, Power BI, D3, React). Frame clinical work as domain context — e.g., 'translated EHR/registry data requirements into reporting specifications for clinical stakeholders' — and quantify scope (datasets, users, reporting cadence). Do not claim engineering experience you do not have; instead position clinical data fluency plus demonstrated tooling as the differentiator.
Skills to highlight
- Data visualization and dashboard design
- SQL and data querying
- Python and/or R for data analysis
- BI tooling (Tableau, Power BI, Looker)
- Front-end/JavaScript visualization libraries (e.g., D3)
- Healthcare data literacy (EHR, genomics, claims, real-world data)
- Stakeholder communication and data storytelling
- Requirements translation between clinical and technical teams
Role summary
A Data Visualization Engineer at Tempus AI would build charts, dashboards, and interactive visual interfaces that make complex data — likely clinical, genomic, or real-world evidence data — usable by internal teams and customers. The posting contains no description, so responsibilities, stack, seniority, and location are unknown.
We publish our own intelligence summary, never the full job description. Always confirm details with the employer when you apply.