Full-Stack / Backend Engineer (React, Python, Data)
5 days ago
Full-Stack / Backend Engineer (React, Python, Data)
Enigmatos - Fleet Cybersecurity | Petah Tiqwa (Hybrid) | Experience: 3+ years |
What we're looking for
- 3+ years of experience as a full-stack or backend engineer
- Solid React + TypeScript experience
- Solid Python (Flask/FastAPI or similar)
- Familiarity with clean architecture principles (SOLID, design patterns, code quality)
- Ability to work across different tools and learn quickly
- Comfortable taking responsibility and owning features end-to-end
- Strong problem-solving skills and ability to reason with real data
What you'll do
You will work across frontend, backend, and data to build the product surfaces our
customers use every day:
Frontend
- Build dashboards, views, and components in React + TypeScript.
- Establish reliable frontend infrastructure: state management, data flows, API
integration.
Backend
- Build Python backend endpoints that power the UI and internal tools.
- Shape insights from existing telemetry, anomalies, and vehicle data.
- Help design and improve APIs consumed by our dashboards.
Data
- Work with large datasets: SQL, aggregation, shaping data for insights.
- Build small/medium data pipelines and contribute to BI and monitoring tools.
- Support system testing views and internal monitoring dashboards.
This is an end-to-end role: sometimes frontend, sometimes backend, sometimes data -
depending on the task.
About Enigmatos
We secure connected fleets - trucks, buses, specialty vehicles against cyber threats. Our
systems process billions of signals in real time, with low latency and high reliability, to keep
vehicles (and the people who rely on them) safe on the road.
We're a small team that values curiosity, collaboration, and pragmatism. If you enjoy solving
real problems and want your work to matter on the road, you'll feel at home here.
Why Enigmatos
- Impact: your work protects critical fleets on real roads
- Ownership: small team, end-to-end responsibility
- Challenge: high-volume data, real-time detections, efficiency at scale
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