Marketing Analytics Engineer - Growth Insights & Dashboards

Gabb Wireless Inc.; Lehi, Northern (UT, KY); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Stock options

401(k) plan with employer match

Hybrid schedule

Generous PTO

Pet insurance

Job summary

Gabb Wireless Inc. is seeking a Marketing Analytics Engineer to bridge data engineering and marketing measurement in Lehi, Utah. You will own analytics infrastructure, model data, build dashboards, and surface insights driving growth for the marketing and growth teams.

You'll work with dbt, SQL, and BI tools (Looker, Tableau, Mode) and integrate data from ad platforms, CRM, ecommerce, and GA4, communicating results clearly to stakeholders while maintaining data quality.

Qualifications

• 2–4 years of analytics engineering / marketing analytics experience.
• Strong SQL and data modeling skills.
• Experience with dbt and modern data warehouses.
• Familiarity with marketing analytics concepts and attribution.
• Experience building dashboards in a BI tool and communicating findings.

Responsibilities

• Own and extend SQL data models for marketing reporting.
• Model data from ad platforms, CRM, ecommerce into reporting layers.
• Build and maintain data pipelines for dashboards and analyses.
• Collaborate on schema design and modeling best practices.
• Surface insights to non-technical stakeholders and drive growth.

Skills

SQL proficiency

dbt

Marketing analytics concepts

BI dashboards

GA4 familiarity

Communication

AI-assisted development

Python (pandas)

Tools

dbt

BI tools (Looker/Tableau/Mode/Metabase)

GA4

Job description

Gabb Wireless Inc. is seeking a Marketing Analytics Engineer to bridge data engineering and marketing measurement in Lehi, Utah. You will own analytics infrastructure, model data, build dashboards, and surface insights driving growth for the marketing and growth teams.

You'll work with dbt, SQL, and BI tools (Looker, Tableau, Mode) and integrate data from ad platforms, CRM, ecommerce, and GA4, communicating results clearly to stakeholders while maintaining data quality.