Building Systems Data Modeler – BMS Deployments

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Noda is a data and analytics company for the commercial built environment. We reimagine how modern buildings operate — because a better world needs better buildings. Better buildings are more efficient, more sustainable, and more resilient. They are intelligent, autonomous ecosystems that anticipate and adapt, seamlessly.

With commercial building operations accounting for nearly 30% of global emissions, we’re on a mission to turn buildings into a force for positive change, powering a more efficient, more sustainable world. We do this with smart software, careful use of modern artificial intelligence, sophisticated data models, and custom interfaces to building systems – and a lot of in-depth knowledge about how commercial buildings actually run.

We’re a young, nimble company where we very much value creative thinking, a love of team work, and a determination to solve the problem, whatever it is. Priorities can shift fast, so adaptability and flexibility come with the territory. The consequence is that you’ll have a chance to make a real impact, backed by a supportive team.

Job Overview

We are seeking an analytical and detail-oriented Building Systems Data Modeler to join our Deployment Team. Reporting to the Senior Deployment Manager, this role plays a critical role in enabling successful deployments of Noda Energy across buildings. This position is responsible for transforming building management system (BMS) data, specifically HVAC, mechanical, and controls information, into high-quality, structured models that drive analytics, energy insights, and fault detection.

In this role, you will interpret complex building data, review mechanical and controls documentation, and apply Noda’s standard Ontology Alignment Project (OAP) framework to create modelled equipment hierarchies, points, and relationships. You will commission analytics, key performance indicators, and reporting features using Noda’s modeling platform, ensuring data accuracy and consistency throughout deployments.

Success in this role requires strong critical thinking, problem solving, and collaboration. You will frequently work with teammates across engineering, deployment, and product functions, contributing to process improvements, sharing knowledge, communicating progress, and helping refine the data modeling methodology.

This is a hands-on technical role, ideal for someone who understands building systems, controls, and data modeling, and is motivated to drive smarter building operations through structured data, analytics, and continuous improvement.

Key Responsibilities

• Lead data modeling of BMS HVAC & controls data for building deployments to deliver Noda Energy, ensuring timely, high quality delivery.

• Deployment of analytics, KPIs, FDD (Fault Detection and Diagnostics), and reporting features.

• Apply critical thinking and problem solving skills to interpret BMS building data and best model the data for the purposes of FDD, energy analysis, and operational optimization.

• Review mechanical systems, major equipment, HVAC plant schematics, BMS graphics.

• Review control drawings, sequences of operation, and BMS configurations to confirm accurate data modeling.

• Understand installations of BACnet gateways and connectivity to customer BMS networks.

• Use Sky Spark and Noda’s data modeling tools to model points, relationships, and equipment hierarchies.

• Collaborate with teammates to share knowledge and grow skills, while sharing best practices and ensuring data quality.

• Apply Noda’s Ontology Alignment Project (OAP) data model to building data, and participate in refinement.

• Create, and enhance documentation to improve processes as the team grows.

• Document progress in project management tools and communicate updates with stakeholders.

• Contribute feedback to Product and Technology teams to improve deployment processes and tools.

Education and Experience

• Bachelor’s degree in Mechanical Engineering, Civil Engineering, or equivalent practical experience in building systems or controls integration.

• New…