Software Engineer, Field & Operational Technology...
Role details
Job location
Tech stack
Job description
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Move quickly, using AI-assisted development where it earns its place, without ever treating speed as an excuse for fragility; and
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Build across priority solution areas including fleet, procurement, project management, and safety.
Own the Architecture and Data Model
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Design the data models, APIs, and application architecture underneath each solution;
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Make the calls on how data is structured, how services talk to each other, and how a tool built for one operating company can generalize across many without collapsing under its own complexity.
Integrate with the Enterprise
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Build integrations and data pipelines against systems of record such as JD Edwards, construction and telematics platforms, and the Databricks lakehouse; and
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Ensure the tools you build read from and write to trusted enterprise data rather than to yet another disconnected copy.
Secure and Operate What You Ship
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Build to Quanta security standards, implementing authentication, two-factor, and role-based access control as a matter of course;
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Own reliability - when something breaks in production, you are the person who understands it and fixes it; and
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Build the logging, monitoring, and documentation that make that possible.
Harden and Make It Maintainable
- Take prototypes and rapidly built proofs of concept and turn them into software a team can maintain - version-controlled, documented, and structured so the next engineer can pick it up; and
Requirements
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7 or more years of professional software development experience, building and shipping applications that real users depend on;
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Strong full-stack ability - comfortable across a modern back end (Python strongly preferred) and a web front end, able to own a feature from database to interface;
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Solid command of relational databases and data modeling, with the judgment to design schemas that hold up as requirements grow;
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Experience designing and building REST APIs and integrating disparate systems, including third-party platforms with imperfect documentation;
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Disciplined engineering practice: fluent with Git-based version control, code review, testing, and thorough documentation as a default rather than an afterthought;
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A practical grasp of application security: authentication, two-factor, role-based access control, and safe handling of sensitive data;
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An ownership mentality - accountable for your code in production, including the parts that are not fun;
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The ability to work directly with non-technical operational and business stakeholders, translating their needs into sound technical decisions; and
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A pragmatic bias toward shipping working software over gold-plating, balanced with the discipline not to leave a mess behind.
Preferred Education and Experience
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Experience with modern cloud data platforms, ideally Databricks (Spark, Delta, Unity Catalog), or a strong equivalent such as Snowflake or a cloud data warehouse preferred;
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Fluency with AI-assisted development tools (such as Claude Code or similar) and good judgment about where they help and where they do not preferred;
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A track record building internal, line-of-business, or operational tools rather than only consumer or shrink-wrapped products preferred;
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Experience taking a self-taught, solo, or prototype codebase and re-architecting it into maintainable, production-grade software preferred;
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Experience as the technical half of a small, high-trust product team, working closely with a single product or operations lead preferred;
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Integration experience with enterprise systems such as JD Edwards, Procore, HCSS, Autodesk, InEight, or telematics platforms preferred; and
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Exposure to construction, utility, energy, or another industrial or field-driven industry a plus.