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Neara is building engineering-grade digital twins of electricity grids using advanced machine learning and physics-enabled simulation. The company helps utilities worldwide understand infrastructure challenges, optimize investments, and build resilient energy systems by simulating extreme weather and structural stress at network-wide scale.
As an Implementation Engineer, you will be part of the Deployment Team responsible for delivering the Neara platform to utility customers globally. Your core responsibilities include:
- Transform raw utility and geospatial data into high-accuracy digital twin models of electricity networks
- Ingest and manipulate massive datasets (LiDAR, GIS, asset databases) using Neara's proprietary schema language and configuration framework
- Perform rigorous QA/QC validation to ensure digital twins accurately reflect real-world physics and customer specifications
- Build custom reports and dashboards within the platform to generate actionable insights for utility engineers
- Contribute to end-to-end platform deployments across utility customers worldwide
- Work closely with Product and Engineering teams to provide feedback on process improvements and tool enhancements
You will work in a hybrid environment from the Vilnius office with flexibility to work remotely. The role offers exposure to cutting-edge digital twin technology, direct impact on global power grid safety and resilience, and opportunities to influence product roadmap and automation of core deployment processes.
REQUIREMENTS:
- Proven experience as a Data Engineer, Implementation Engineer, Integration Engineer, Software Engineer, or similar role
- Proficiency in at least one major programming language (SQL, Python, or similar) with demonstrated ability to learn new languages
- Comfortable learning and mastering a new schema language to manipulate data and build reports
- Excellent written communication skills with experience contributing to internal knowledge bases and external user manuals
- Ability to articulate technical configurations clearly to diverse audiences in fluent English
- Background in engineering, mathematics, software engineering, computer science, or related field (preferred)
- Familiarity with GIS, CAD geoprocessing, or LiDAR data beneficial but not required
- Ability to break down complex data discrepancies and systematically reconfigure models for 100% accuracy
