Senior Data Engineer

LVT•American Fork, UT

9h•Onsite

About The Position

As Senior Data Engineer, you will own and evolve LVT’s core data platform—architecting and operating the pipelines, transformations, and semantic models that power reporting, analytics, and business decisions at scale. This is a high-impact individual contributor role: your technical decisions will influence company-wide systems and competitive positioning, not just team-level outputs. You’ll lead cross-functional data initiatives, set engineering standards, and contribute to the data infrastructure that supports LVT’s growing AI capabilities. This role is based in-office out of our Headquarters in American Fork, Utah.

Requirements

7+ years building and operating production data pipelines using SQL, Python, and modern ELT tooling (dbt, Fivetran, Airflow, or equivalents). You’ve owned systems under pressure and know how to build for long-term reliability.
Expert-level Snowflake experience—performance optimization, dynamic tables, data security, and Cortex familiarity. You know when and why to use each capability.
Proven ability to design and maintain semantic or metrics layers that enforce consistent business logic across a complex, multi-team organization.
You operate at the level of organizational strategy—your work influences competitive positioning, not just sprint delivery. You define standards, evaluate trade-offs, and build for the long term.
Reliability is non-negotiable. You instrument pipelines with observability, validation, and alerting from day one, and you define the standards others follow.
You own work from scoping through production and beyond. You influence company-wide technology decisions and mentor others along the way—without waiting to be told what to do.
Familiar with AI/ML data patterns—RAG architectures, vector stores, embedding pipelines—and able to build the data infrastructure those systems require.
You build partnerships with executives and cross-functional stakeholders, translating complex technical trade-offs into clear recommendations that earn trust and drive adoption.

Responsibilities

Design, build, and maintain scalable, production-grade ELT pipelines that move data reliably from diverse source systems into a clean, well-governed data platform.
Architect and own LVT’s Snowflake environment—performance tuning, dynamic tables, clustering strategies, storage optimization, and cost governance.
Develop and enforce semantic models that expose consistent, trusted business definitions across all reporting and analytics surfaces.
Define and drive data engineering standards that improve quality, reliability, and productivity across teams—not just within BI.
Lead cross-functional data initiatives, partnering with engineering, finance, operations, and product to deliver solutions that drive meaningful organizational outcomes.
Establish data quality infrastructure—implement validation, monitoring, and alerting frameworks that surface problems before they reach stakeholders.
Contribute to AI data infrastructure—support RAG pipelines, vector storage, and Snowflake Cortex integrations as one component of the broader engineering scope.
Mentor junior engineers and build strong partnerships with executives and business stakeholders to drive adoption of data solutions.