Senior Data Analytics Engineer
Confidential
Posted: April 9, 2026
Interested in this position?
Create a free account to apply with AI-powered matching
Quick Summary
Senior Data Analytics Engineer
Required Skills
Job Description
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’re looking for a Senior Data Analytics Engineer to take ownership of our BI ecosystem and drive high-impact improvements in data reliability, performance, and business insights.
This role sits at the intersection of data engineering, analytics, and business strategy, working closely with Marketing and cross-functional teams to ensure data is not only accurate — but actionable.
You’ll play a key role in transforming how the company uses data to make decisions.
• Own and improve the reliability and performance of dashboards and reporting systems
• Design and optimize data models and SQL transformations in the data warehouse
• Build and maintain scalable BI solutions using Tableau and cloud data platforms
• Implement data quality checks, monitoring, and anomaly detection systems
• Partner with stakeholders to translate business needs into robust data products
• Improve query performance and reduce reporting inefficiencies
• Define and standardize KPI frameworks, especially for Marketing metrics
• Ensure documentation, ownership, and governance across all BI assets