Senior Data Analyst – French/English Proficiency Required

Accountabilities:: Business Intelligence & Reporting: Design, build, and maintain dashboards, reports, and analytical tools using platforms such as Looker, Sigma, Tableau, Power BI, or similar technologies. Business Insights: Partner with Product, Operations, Marketing, Finance, Customer Success, and Leadership teams to deliver analysis that informs strategic and operational decisions. Product Analytics: Analyze customer and user behavior across activation, conversion, engagement, retention, churn, and feature adoption to identify opportunities and performance trends. Funnel & Performance Analysis: Identify product opportunities, friction points, funnel drop-offs, and emerging trends using appropriate analytical methods, while contributing to metric definitions and performance tracking. Reporting Automation: Automate recurring reports and data workflows using SQL, dbt, and lightweight scripting tools such as Python, R, Google Apps Script, or similar technologies. Data Quality: Support the accuracy, consistency, and reliability of reporting pipelines, data marts, dashboards, and underlying analytical data. Partner-Facing Analytics: Develop custom data solutions and insights for business customers, including presenting findings, explaining analysis, answering questions, and identifying opportunities in both French and English. Cross-Functional Collaboration: Work closely with Customer Success, Product, Marketing, Finance, Data, and Software Engineering teams to support analytics projects and improve the reliability and commercial value of data. AI-Enabled Analytics: Use modern AI tools and APIs, including platforms such as OpenAI, Claude, Gemini, or comparable solutions, to accelerate analysis, automate workflows, and improve stakeholder self-service. AI Experimentation & Validation: Explore use cases such as natural-language data analysis, automated insight generation, data-quality checks, opportunity identification, and workflow automation while validating AI outputs for accuracy, privacy, and business relevance. Analytics Community: Share best practices, contribute to analytics initiatives and forums, and stay informed about emerging developments in data analytics and AI. Requirements Professional Experience: 3–5 years of experience in business intelligence, product analytics, data analytics, or a closely related field. Language Proficiency: Business-level fluency in both French and English is required, with the ability to communicate effectively in professional, cross-functional, and client-facing settings. Client-Facing Skills: Comfortable presenting insights, explaining analytical findings, answering questions, and engaging directly with business customers. Analytical Mindset: Curious, data-driven, and capable of translating complex datasets and analyses into clear, practical recommendations. Technical Skills: Experience working with SQL, BI and reporting platforms, and data workflows; familiarity with dbt and lightweight scripting using Python, R, Google Apps Script, or similar tools is valuable. Product & Business Understanding: Ability to connect analytical findings to customer behavior, product performance, business priorities, revenue opportunities, and operational improvements. AI Fluency: Comfortable using modern AI tools thoughtfully, evaluating their outputs, and identifying practical applications for analytics, automation, and self-service. Communication: Strong written and verbal communication skills, with the ability to adapt complex technical information to both technical and non-technical audiences. Collaboration: Able to work effectively with multidisciplinary teams and manage analytics projects with attention to quality, deadlines, and stakeholder needs. Judgment & Ownership: Strong attention to data accuracy, privacy, and reliability, with the judgment to validate AI-generated or analytical insights before they are used to support business decisions. Benefits Compensation: Monthly compensation range of MX$80,000–MX$85,000 , with equity offered. Remote Work: Remote working arrangement. Full-Time: Full-time employment within an engineering and analytics-focused environment. Cross-Functional Exposure: Opportunity to collaborate with Product, Operations, Marketing, Finance, Customer Success, Leadership, Data, and Software Engineering teams. Customer Impact: Direct opportunity to deliver insights and analytics solutions that help business customers make better decisions and identify opportunities. AI & Innovation: Hands-on exposure to modern AI tools and emerging applications of AI within analytics workflows. Professional Growth: Opportunity to contribute to analytics best practices, experiment with new approaches, and develop expertise across business intelligence, product analytics, and AI-enabled analytics.