Data Engineer

ABOUT LVT

LVT is redefining how businesses operate in the physical world, moving beyond traditional security solutions to deliver AI-driven, actionable intelligence that makes sites smarter, safer, and more secure. Since pioneering our first mobile, solar-powered units, our commitment to scrappy, hands-on innovation has made us an established leader and one of the fastest-growing companies in intelligent site technology. We are building the next generation of solutions—from our physical units in the field to a powerful Agentic AI platform—that allows our customers to gain unprecedented visibility and control over safety, compliance, and operations. This is your chance to join a cutting-edge team that isn't just watching the world change, but actively building the technology that is changing it.

We’re a team that’s focused on growth and innovation, and we’re proud that our crew, products, and leadership are being recognized for it.

• A Top-Tier Growth Company: Named one of the Financial Times’ Fastest Growing Companies 2025 and #10 on the Inc. 5000 Rocky Mountain Regional list for 2025.
• Innovative Leadership: Our CEO, Ryan Porter, was named an EY Entrepreneur of the Year 2025, and our CTO, Steve Lindsey, was inducted into the Silicon Slopes CTO Hall of Fame in 2024.
• Product & Software Excellence: We were named one of The Software Report’s Top 100 Software Companies of 2023 and are a winner of the Security Today Govies Award for 2025.

ABOUT THIS ROLE

As Data Engineer, AI, you will play a key role in building and advancing LVT’s data platform — contributing across the full data engineering lifecycle, from ingestion and transformation to semantic modeling and delivery — while also helping build the data infrastructure that powers LVT’s AI initiatives, including RAG pipelines and Snowflake Cortex models. This is a core engineering role with an AI edge: you’ll keep the data platform running with precision and reliability, and you’ll be the person who makes sure our AI systems have the clean, well-structured data they need to perform.

LVT is a flexible-first company. This role can be performed remotely, with a preference for candidates who can work from our American Fork, UT office.

ROLE RESPONSIBILITIES

• Design, build, and maintain scalable ELT pipelines that move data reliably from source systems into a clean, well-governed data platform.
• Develop and maintain semantic models that expose consistent, trusted business definitions across reporting and analytics surfaces.
• Own data quality — implement validation, monitoring, and alerting frameworks that catch problems before they reach stakeholders.
• Optimize Snowflake performance across ingestion, transformation, and storage, including dynamic tables, clustering, and query tuning.
• Architect and build the data infrastructure required for RAG applications, including vector storage, chunking strategies, and retrieval pipelines.
• Collaborate with AI/ML engineers to support Snowflake Cortex model development with well-structured, context-rich training and inference data.
• Partner with analytics engineers, data scientists, and business stakeholders to translate requirements into durable data solutions.
• Document data architecture, pipeline design, and modeling decisions to support team knowledge and long-term maintainability.

OUR IDEAL CANDIDATE

• Data Engineering Foundation: 5+ years building and maintaining production-grade pipelines using SQL, Python, and modern ELT tools such as dbt, Fivetran, or Airflow.
• Snowflake Proficiency: Deep hands-on experience with Snowflake, including performance optimization, dynamic tables, and familiarity with Cortex AI capabilities.
• Semantic Modeling Experience: Ability to design and maintain semantic or metrics layers that enforce consistent business logic across the organization.
• AI Infrastructure Awareness: Working knowledge of RAG architectures and the data patterns — chunking, embedding, retrieval — that support LLM-driven applications.
• Data Quality Ownership: Strong instinct for reliability — you instrument pipelines with observability and validation from the start.
• End-to-End Mindset: Comfortable owning work from scoping through production — you define the problem, build the solution, and stand behind the outcome.
• Collaborative Communicator: Able to work fluidly with eng