Implementation Engineer

The role

You will transform raw utility and geospatial data into high accuracy digital twin models of electricity networks. You will join the Deployment Team to deliver the Neara platform to utility customers worldwide.

What you will do

• Contribute to the end-to-end deployment of the Neara platform for utility customers worldwide.
• Ingest and manipulate massive datasets using Neara’s schema language and configuration framework.
• Perform rigorous QA/QC to ensure the digital twin accurately reflects real-world physics and customer specifications.
• Build custom reports and dashboards within the platform to drive actionable insights for utility engineers.
• Work closely with Product and Engineering to provide feedback on process and tool improvements.

Required qualifications

• Proven experience as a Data Engineer, Implementation Engineer, Integration Engineer, Software Engineer, or similar role.
• Proficiency in at least one major language such as SQL, Python, or similar.
• Demonstrated ability to learn a new language.
• Ability to learn and master a new schema language to manipulate data and build reports.
• Excellent written communication skills.
• Experience contributing to internal knowledge bases and external user manuals.
• Ability to articulate technical configurations clearly to diverse audiences in fluent English.
• The ability to break down complex data discrepancies and systematically reconfigure models to ensure 100% accuracy.

Nice to have

• A background in engineering, electrical engineering, mathematics, software engineering, computer science, or a related field
• Familiarity with GIS, CAD geoprocessing, or LiDAR data

Benefits

• Work directly impacts the safety and reliability of global power grids.
• Gain expert-level proficiency in an engineering-grade 3D modeling environment.
• Exposure to the cutting edge of Digital Twin technology.
• Opportunities to influence the product roadmap and automate core deployment processes.

About the company

Neara uses advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents. The team utilizes AI and machine learning to accelerate data classification and complex scenario analysis.