Senior Data Analytics Lead (Remote)

Ruby Labs Ltd; Polska; A distancia; PLN 180.000 - 240.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Unlimited PTO

Paid holidays

MacBook provided

Contractor-friendly agreement

Descripción de la vacante

Ruby Labs is hiring a Lead Data Analyst to drive analytics for subscription products and web funnels. You will partner with Product, Marketing, and Data teams to improve conversion, retention, and LTV, while ensuring trusted tracking and robust data models.

This hands-on, cross-functional role involves problem framing, recommendation, and mentoring analysts, with collaboration across Data Engineering/BI to keep data foundations reliable.

Formación

• Degree in an analytical field or equivalent practical experience.
• 3+ years of experience as a Data Analyst with end-to-end ownership.
• Experience in subscription business and/or web funnels.

Responsabilidades

• Define KPIs and decision criteria with Product, Marketing, and Data teams.
• Create dashboards and reports (Product Reports, Marketing Performance Reports) with clear, trusted data.
• Conduct full-funnel analysis, identify bottlenecks, propose improvements or A/B ideas.
• Lead user behavior analysis (journeys, drop-offs, activation) using event data.
• Monitor metrics and communicate updates with SLAs to stakeholders.
• Design and maintain event taxonomy and tracking structure; validate data logic.
• Build robust, reusable SQL data models with performance-minded queries.
• Mentor junior/middle analysts in SQL, funnel analysis, and experimentation quality.

Conocimientos

Data analysis

End-to-end ownership

Product analytics

A/B testing

SQL

BI tools

Communication

English

Educación

Degree in analytical field

Herramientas

Mixpanel

GA4

Amplitude

Tableau/Looker

BigQuery

Python/R

GCP

Descripción del empleo

Ruby Labs is hiring a Lead Data Analyst to drive analytics for subscription products and web funnels. You will partner with Product, Marketing, and Data teams to improve conversion, retention, and LTV, while ensuring trusted tracking and robust data models.

This hands-on, cross-functional role involves problem framing, recommendation, and mentoring analysts, with collaboration across Data Engineering/BI to keep data foundations reliable.