[Hiring] Senior Data Analytics Engineer @Trafilea

Role Description

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.

Job 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.

Qualifications

• 4+ years in Data Engineering, Analytics Engineering, BI, or ML Engineering in production environments.
• Advanced SQL proficiency (joins, CTEs, window functions, optimization) and proven experience designing/maintaining production data models and pipelines.
• Hands-on experience with core AWS data services (e.g., Redshift, S3, Glue, Athena, Lambda).
• Hands-on experience with Apache Airflow for workflow management.
• Strong Python skills (OOP focus), experience with CI/CD practices (GitHub Actions/GitLab), and containerization (Docker, Kubernetes/ECS/EKS).
• Proficiency with BI platforms (Tableau, Quicksight or similar) and direct ownership of production reporting, data quality, and root-cause analysis.
• 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).