CX Analytics Engineer — Remote, Stock Options

Eneba Games; United States; A distancia; USD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Employee Stock Options

Performance bonuses

Learning budget

Volunteer opportunities

Remote work option

Descripción de la vacante

Eneba Games is hiring a Data Analytics Engineer for the Customer Support team. You’ll build scalable data models, map sources, design metrics, and own dashboards that drive action. Collaborate with product, engineering and risk to quantify impact and inform fixes.

A strong focus on AI, automation and self-service helps scale support operations. You’ll turn insights into operational changes with stakeholders and monitor CSAT, SLA and volumes to spot trends and drive improvements.

Formación

• 3+ years of experience as a Data Analytics Engineer in CX or similar.
• Strong SQL, dbt and hands-on experience with BI/reporting tools.
• Solid knowledge of customer support metrics and actioning insights.

Responsabilidades

• Build and maintain dbt models across data layers with tests and docs.
• Map data sources, audit tagging and join data for reliable reporting.
• Define metrics like repeat contact and cost per contact with raw data proof.
• Develop dashboards end-to-end in QuickSight and Omni and deliver weekly packs.
• Monitor volumes, SLAs and CSAT; investigate anomalies in the data flow.
• Analyze feedback to surface coaching needs and process gaps.
• Measure AI/bot impact on issue resolution and self-service.
• Collaborate with Product, Payments and Risk to quantify fixes.
• Forecast contact volume to assist capacity planning.

Conocimientos

SQL

dbt

BI tools

Herramientas

Databricks

Kustomer

QuickSight

Mixpanel

Jira

Slack

Descripción del empleo

Eneba Games is hiring a Data Analytics Engineer for the Customer Support team. You’ll build scalable data models, map sources, design metrics, and own dashboards that drive action. Collaborate with product, engineering and risk to quantify impact and inform fixes.

A strong focus on AI, automation and self-service helps scale support operations. You’ll turn insights into operational changes with stakeholders and monitor CSAT, SLA and volumes to spot trends and drive improvements.