Senior Data Analytics Engineer

OpenKrill; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Trafilea, a consumer tech platform, is seeking a data/analytics engineer to architect and scale data pipelines, models, and BI tooling across the AWS stack.

You will own data quality, governance, and production reporting, partnering with Marketing Science, Analytics, and commercial teams to operationalize ML models and drive metrics like CAC, ROAS, and LTV.

This role is 100% remote, offering a competitive USD salary and opportunities to impact global brands.

Qualifications

• 4+ years in Data Engineering, Analytics Engineering, BI, or ML Engineering in production environments.
• Strong SQL proficiency (joins, CTEs, window functions) and production data models.
• Hands-on experience with core AWS data services (Redshift, S3, Glue, Athena, Lambda).
• Airflow for workflow management; Python with CI/CD and Docker/Kubernetes.

Responsibilities

• Architect, scale, and maintain end-to-end ETL/ELT pipelines and Airflow-driven workflows across data lifecycle.
• Design and optimize SQL transformations, datasets, and data models; build dashboards and analytical tools.
• Establish governance, monitoring, SLAs, data validation, and anomaly detection for trusted metrics.
• Operationalize ML models in batch/real-time environments and support Marketing Science and analytics teams.
• Optimize SQL and data pipelines for performance, cost, and scalability on AWS.
• Collaborate with cross-functional teams to define and report core metrics (CAC, ROAS, LTV).

Skills

Data Engineering

Analytics Engineering

BI

ML Engineering

SQL

Python

Airflow

AWS

Docker

Kubernetes

CI/CD

Tableau

Quicksight

Data Modeling

Data Pipelines

Data Governance

Communication

Tools

Redshift

S3

Glue

Athena

Lambda

dbt

Tableau

Quicksight

Job description

About TrafileaTrafilea 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 TrafileaWe’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 ResponsibilitiesThis 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).