Data Analyst II

LVT•American Fork, UT

7d•Onsite

About The Position

LVT is looking for a Data Analyst to turn raw operational and go-to-market data into decisions our teams can act on. You'll own Tableau dashboarding and reporting for GTM and Service Operations, surface trends across sales, customer service, and field operations, and partner directly with stakeholders across the business to answer their hardest data questions. This is a chance to build foundational analytics muscle at a company scaling fast, with real visibility into how your work shapes strategy. This role is based out of our American Fork, UT office.

Requirements

2–3 years of experience in a data analyst or similar analytics role.
Strong SQL skills and comfort working with large, often messy datasets.
Able to translate complex data findings into clear takeaways for non-technical stakeholders.
Takes initiative on identifying data issues and improvement opportunities without being told.
Understands how GTM and Service Operations data connects to real revenue and customer outcomes, not just the numbers themselves.
Comfortable with BI/visualization software used to build complex custom reports that convey data in a clean visually appealing way; prior Tableau experience is a plus but not required.
Catches errors and inconsistencies in data before they become someone else's problem.

Nice To Haves

prior Tableau experience is a plus but not required.

Responsibilities

Build and maintain Tableau dashboards and recurring reports that give GTM and Service Operations leaders real-time visibility into key metrics.
Design SQL queries and data pipelines to pull, clean, and structure data from multiple internal systems.
Partner with Sales, Marketing, and Service Operations teams to identify metrics that matter and translate business questions into analysis.
Own data quality checks, flagging and resolving discrepancies before they reach stakeholders.
Deliver ad hoc analyses that inform decisions on pipeline, service performance, and operational efficiency.
Document data definitions and reporting logic to keep GTM and Service Ops analytics consistent and auditable.
Identify trends and anomalies in GTM and service data, surfacing insights proactively rather than waiting to be asked.
Support experimentation and measurement efforts by structuring test data and validating results.