Analytics Engineer: AI-Driven Contact Center Insights

Cricut; South Jordan (UT); On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Medical, Dental, Vision coverage

401(k) match

Generous PTO

Tuition reimbursement

Lifestyle stipend

Employee discounts

Job summary

Cricut is seeking an Analytics Engineer to join the Corporate BI team. You will own end-to-end data workflows for Customer Care data, from sourcing to dashboards, enabling actionable insights that improve contact center performance and customer experience.

You’ll build analytical models, translate business needs into scalable data solutions, and work with multiple platforms to ensure trusted data and impact across the organization.

Qualifications

• Bachelor’s degree in Data Science, CS, Statistics, Information Systems or equivalent.
• 3-5 years of experience in data analytics, analytics engineering, or a related role.
• Strong SQL skills with experience in tables, views, and transformations.
• Experience with data from contact center systems (ACD, CRM, ticketing, chat).
• Experience with ETL/ELT and data visualization tools.

Responsibilities

• Design, build, and maintain analytical datasets and tables for reporting and forecasting.
• Ingest and transform data from contact center systems into clean, structured datasets.
• Own end-to-end analytics workflow from source to dashboards and insights.
• Analyze performance metrics and produce recurring and ad-hoc reports.
• Develop AI/analytic insights from transcripts, surveys, and feedback sources.

Skills

SQL

Data analysis

Data engineering

ETL/ELT

Data visualization

Education

Bachelor’s degree in Data Science/CS/Statistics or related

Tools

Domo

Tableau

Power BI

AWS/Snowflake

Job description

Cricut is seeking an Analytics Engineer to join the Corporate BI team. You will own end-to-end data workflows for Customer Care data, from sourcing to dashboards, enabling actionable insights that improve contact center performance and customer experience.

You’ll build analytical models, translate business needs into scalable data solutions, and work with multiple platforms to ensure trusted data and impact across the organization.