CUJO AI®

Analytics Engineer

• Partner with Product, Engineering and business teams to turn questions into analyses, metrics and data models.
• Deliver ad hoc deep dives, recurring KPI reports and dashboards.
• Define, validate and document KPIs with stakeholders, and help teams use them consistently in planning and decisions.
• Build and maintain tested, documented data models and ELT transformations with the Data Platform team.
• Create curated datasets, dashboards and templates for self-service analytics.
• Take metrics and models from prototype through production and ongoing maintenance.
• Streamline analytics practices across analysts in other teams through shared modeling conventions, metric definitions, code review, onboarding and coaching.
• Prioritize requests from multiple teams, balancing urgent needs with reusable data assets.
• Identify gaps in data, instrumentation or tooling and work with engineering to close them.
• Present findings clearly to technical and non-technical audiences.

Explore Senior Data Analyst, Analytics Engineering at CUJO AI®. Review requirements and application details.

Senior Data Analyst, Analytics Engineering

• Partner with Product, Engineering and business teams to turn questions into analyses, metrics and data models
• Deliver ad hoc deep dives, recurring KPI reports and dashboards
• Define, validate and document KPIs with stakeholders and help teams use them consistently
• Build and maintain tested, documented data models and ELT transformations with the Data Platform team
• Create curated datasets, dashboards and templates for self-service analytics
• Take metrics and models from prototype through production and ongoing maintenance
• Streamline analytics practices across analysts through shared modeling conventions, metric definitions, code review, onboarding and coaching
• Prioritize requests from multiple teams while balancing urgent needs with reusable data assets
• Identify gaps in data, instrumentation or tooling and work with Engineering to close them
• Present findings clearly to technical and non-technical audiences

• Partner with Product, Engineering and business teams to turn questions into analyses, metrics and data models
• Deliver ad hoc deep dives, recurring KPI reports and dashboards
• Define, validate and document KPIs with stakeholders, and help teams use them consistently in planning and decisions
• Build and maintain tested, documented data models and ELT transformations with the Data Platform team
• Create curated datasets, dashboards and templates for self-service analytics
• Take metrics and models from prototype through production and ongoing maintenance
• Streamline analytics practices across analysts in other teams through shared modeling conventions, metric definitions, code review, onboarding and coaching
• Prioritize requests from multiple teams, balancing urgent needs with reusable data assets
• Identify gaps in data, instrumentation or tooling and work with engineering to close them
• Present findings clearly to technical and non-technical audiences