Senior Data Analytics Engineer

Posted 10 Days Ago
Be an Early Applicant
3 Locations
In-Office or Remote
Senior level
Artificial Intelligence • Big Data • Information Technology • Analytics
Next Generation Consumer-Tech Platform
The Role
Architect and maintain end-to-end ETL/ELT pipelines, Airflow workflows, production data models, BI reporting, and ML infrastructure. Ensure data quality through governance, monitoring, validation, anomaly detection, and root-cause analysis. Optimize SQL workloads and AWS data platforms for performance, cost, and scalability. Partner with marketing, analytics, commercial, and executive stakeholders to define metrics such as CAC, ROAS, LTV, and conversion funnels. Build internal data tools and operationalize machine learning models.
Summary Generated by Built In
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 D2C brands (not an agency), with a presence in Walmart, Nordstrom, Amazon, and a strong global 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.

Job Responsibilities

This role sits at the intersection of data engineering, analytics, business intelligence, and machine learning infrastructure. You will architect and scale modern data pipelines, build resilient data models, and ensure the reliability, accuracy, and operational performance of our BI reporting layer and ML platforms.

Key Responsibilities

  • Pipeline & System Architecture: Architect, scale, and maintain end-to-end ETL/ELT pipelines and Airflow-driven workflows across the full data lifecycle (extraction transformation ML modeling reporting).

  • Data Modeling & BI Delivery: Design and optimize SQL transformations, datasets, and high-quality data models. Build, centralize, and maintain dashboards and analytical tools to translate business needs into scalable BI solutions.

  • Data Quality & Governance: Establish strong governance, monitoring, alerting, SLAs, data validation, and anomaly detection. Perform root-cause analysis to ensure high accuracy, reliability, and business trust in metrics.

  • Machine Learning & Analytics Support: Operationalize ML models in batch/real-time environments and build internal data tools to empower Marketing Science, Analytics, and commercial teams.

  • Performance & Cost Optimization: Optimize complex SQL queries and large-scale datasets for performance, cost-efficiency, and scalability across the AWS cloud ecosystem.

  • Stakeholder Collaboration: Partner with cross-functional teams to define and report on core business metrics (e.g., CAC, ROAS, LTV, conversion funnels) to directly guide executive decision-making.

  • Experience: 4+ years in Data Engineering, Analytics Engineering, BI, or ML Engineering in production environments.

  • SQL & Modeling: Advanced SQL proficiency (joins, CTEs, window functions, optimization) and proven experience designing/maintaining production data models and pipelines.

  • AWS Stack: Hands-on experience with core AWS data services (e.g., Redshift, S3, Glue, Athena, Lambda).

  • Orchestration: Hands-on experience with Apache Airflow for workflow management.

  • Programming & Engineering Standards: Strong Python skills (OOP focus), experience with CI/CD practices (GitHub Actions/GitLab), and containerization (Docker, Kubernetes/ECS/EKS).

  • BI & Data Quality: Proficiency with BI platforms (Tableau,Quicksight or similar) and direct ownership of production reporting, data quality, and root-cause analysis.

  • Soft Skills: Systems-level thinker with high standards for documentation, scalability, precision, and communicating insights to technical and non-technical partners.

Nice-to-Have:

  • Experience with dbt or modern ELT frameworks

  • Specialized e-commerce and marketing analytics expertise (CAC, ROAS, LTV, retention, and funnel optimization).

Skills Required

  • 4+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or Machine Learning Engineering in production environments
  • Advanced SQL proficiency, including joins, CTEs, window functions, and query optimization
  • Experience designing and maintaining production data models and pipelines
  • Hands-on experience with AWS data services, including Redshift, S3, Glue, Athena, or Lambda
  • Hands-on experience with Apache Airflow for workflow management
  • Strong Python skills with an object-oriented programming focus
  • Experience with CI/CD practices using GitHub Actions or GitLab
  • Experience with containerization using Docker, Kubernetes, ECS, or EKS
  • Proficiency with BI platforms such as Tableau or QuickSight
  • Direct ownership of production reporting, data quality, and root-cause analysis
  • Experience with dbt or modern ELT frameworks
  • Specialized e-commerce and marketing analytics expertise, including CAC, ROAS, LTV, retention, and funnel optimization
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The Company
HQ: Montevideo
437 Employees
Year Founded: 2014

What We Do

Trafilea is a consumer tech platform business leveraging AI, advanced analytics, proprietary technology, and proven world-class marketing to build and scale category-defining brands in women’s intimates, beauty, and wellness — primarily for the U.S. market. We are a remote data-driven team of ambitious doers, passionate marketers, and tech innovators with the instincts and energy to transform the world as we know it.

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