Analytics Engineer @ Rentcars
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Job Details
Overview
Rentcars is Latin America's largest car rental platform and a global leader in the industry. With operations in over 160 countries, our headquarters in Curitiba (PR) and Amsterdam drive our commitment to excellence and innovation. We are a Great Place to Work® certified organization and a B-Corp, dedicated to sustainability, diversity, and the well-being of our Renties.
Role Responsibilities
- Develop Data Marts and integrate diverse data sources
- Execute data cleaning, pre-processing, and performance optimization
- Identify patterns, trends, and correlations through statistical analysis
- Create dashboards, reports, and visualizations for decision making
- Collaborate with high performance teams to align deliverables and roadmaps
What We Expect
- Graduation in Statistics, Data Science, Engineering, Marketing, Economics or related fields
- At least 4 years of experience in data analysis and engineering
- Proficient in Python, DBT, and ETL processes
- Experience in dimensional modeling, data warehouse techniques, CI/CD, and observability
- Expertise in Tableau/Metabase and data storytelling methods
- Strong communication skills and a proactive, collaborative mindset
Benefits
Our flexible benefits program, Beneflex, offers base benefits at no cost plus points to allocate across various options. Standard benefits include health insurance, life insurance, meal vouchers, and transport options. Additional perks include pet health, dental, fitness, financial organization, cultural benefits, and more. For on-site employees, enjoy fresh fruits, coffee, de-stress zones, and social events.
Key skills/competency
- Data Integration
- Python
- ETL
- DBT
- Data Warehousing
- Dashboard Development
- Statistical Analysis
- Data Visualization
- CI/CD
- Data Governance
How to Get Hired at Rentcars
🎯 Tips for Getting Hired
- Customize your resume: Highlight data integration and Python expertise.
- Study Rentcars culture: Understand their global and sustainable approach.
- Emphasize project experience: Showcase data warehouse and ETL projects.
- Prepare for technical questions: Review SQL, Python, and data visualization.