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Neara

Physics-based digital twin platform for infrastructure

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeVilnius, Vilnius City Municipality, Lithuania€3k - €4k /mo

About the Job

Requirements

  • Proven experience as a Data Engineer, Implementation Engineer, Integration Engineer, Software Engineer, or in a similar role.
  • Proficiency in at least one major language, such as SQL or Python, and demonstrated ability to learn a new language, including a schema language for manipulating data and building reports.
  • Fluent English and strong written communication skills, including experience contributing to internal knowledge bases and external user manuals, and the ability to explain technical configurations to diverse audiences.
  • Ability to break down complex data discrepancies and systematically reconfigure models to ensure accuracy.

Responsibilities

  • Contribute to the end-to-end deployment of the Neara platform for utility customers worldwide.
  • Ingest and manipulate large datasets, including LiDAR, GIS, and asset databases, using Neara's schema language and configuration framework.
  • Perform quality assurance and quality control to ensure the digital twin accurately reflects real-world physics and customer specifications.
  • Build custom reports and dashboards within the platform to provide actionable insights for utility engineers.
  • Work with Product and Engineering to provide feedback on process and tool improvements that speed up future deployments.

Desired Qualifications

  • A background in engineering, mathematics, software engineering, computer science, or a related field is preferred.
  • Familiarity with GIS, CAD geoprocessing, or LiDAR data can help accelerate learning of the platform.

About the Company

Neara

Physics-based digital twin platform for infrastructure

Neara builds a SaaS platform that creates a precise 3D digital twin of entire infrastructure networks. It fuses GIS data, LiDAR imagery, and engineering specifications to produce an engineering-grade model of the network. The platform uses physics-based simulations and AI to test asset behavior under real-world scenarios, helping utilities anticipate risks, optimize maintenance, and plan upgrades. It differentiates by applying rigorous, cross-sector physics models at scale for major utilities, with a goal to expand internationally and extend into telecom and public transportation to support grid reliability and the energy transition.

Company size
201-500
Company stage
Series D
Total funding
$114.9M
Headquarters
Sydney NSW, Australia
Founded
2016

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