Senior Analytics Engineer
About Trafilea
Trafilea is a Consumer Tech Platform for Transformative Brand Growth. We’re building the AI Growth Engine that powers the next generation of consumer brands.
With over $1B+ in cumulative revenue, 12M+ customers, and 500+ talents across 19 countries, we combine technology, growth marketing, and operational excellence to scale purpose-driven, digitally native brands.
We own and operate our own digitally native brands (not an agency), with presence in Walmart, Nordstrom, and Amazon, and a strong global D2C footprint.
Why Trafilea
We’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.
🚀 We build and scale our own brands.
🦾 We invest in AI and automation like few others in eCom.
📈 We test fast, grow fast, and help you do the same.
🤝 Be part of a dynamic, diverse, and talented global team.
🌍 100% Remote, USD competitive salary, paid time off, and more.
Key Responsibilities
We are looking for a Senior Analytics Engineer who can provide expertise to build and maintain data models for new and existing products in the company’s data platform, that will impact directly on Trafilea’s growth. Must be passionate about data reporting and analytics, to create scalable and reliable frameworks to ensure cost-effective and accurate data shared with stakeholders.
Analysis, Design, implementation, and maintenance reports that produce business-critical data reliably and efficiently using cloud technologies.
Understand ETLs, using the current Apache Airflow. Propose new initiatives to improve performance, scalability, reliability, and overall robustness on metrics.
Collect, process, and clean data from different sources using SQL & TABLEAU.
Work side by side with the main Architects and Developers to create and ensure best practices and guidelines are being used properly by all projects.
Assess and communicate effectively the effort for required developments.
Discover new data sources to improve new and existing data pipelines. Be in charge of building and maintaining data pipelines and data models for new and existing projects.
Maintain detailed documentation of your work and changes to support data quality and governance.
Provide feedback and expert points of view as needed to help thrive all data initiatives in the company.
Create benchmark control of execution times for every pipeline, to control and identify potential availability issues.