Role description
Job Summary
We are looking for a highly analytical and business-driven Data Analyst with strong expertise in SQL, Tableau, and monetization analytics. The ideal candidate will partner with cross-functional stakeholders to generate insights, optimize revenue streams, and drive data-backed decision-making.
Key Responsibilities
Data Analysis & SQL
- Extract, clean, and analyze large datasets using advanced SQL queries
- Build complex queries to track user behavior, revenue performance, and business KPIs
- Perform cohort analysis, funnel analysis, and A/B test evaluations
Visualization & Reporting (Tableau)
- Design and develop interactive dashboards in Tableau for real-time business insights
- Translate complex data into clear, actionable visual stories
- Maintain and optimize dashboards for performance and usability
Monetization & Revenue Analytics
- Analyze user journeys and identify opportunities to improve revenue and monetization strategies
- Monitor key metrics such as ARPU, conversion rates, retention, and LTV
- Support pricing strategy, subscription models, or ad revenue optimization
- Provide data-driven recommendations to increase revenue and improve unit economics
Stakeholder Management
- Collaborate with Product, Business, Marketing, and Finance teams
- Gather business requirements and translate them into analytical solutions
- Communicate insights and recommendations clearly to both technical and non-technical stakeholders
- Present findings to leadership and drive action plans
Required Skills
- Strong proficiency in SQL (joins, window functions, CTEs, query optimization)
- Hands-on experience with Tableau (dashboard creation, data modeling, storytelling)
- Experience in monetization/revenue analytics or business performance analysis
- Excellent analytical and problem-solving skills
- Strong communication and stakeholder management skills
Preferred Qualifications
- Experience in digital products / e-commerce / SaaS / fintech / ad-tech
- Knowledge of Python/R for advanced analysis
- Familiarity with A/B testing frameworks
- Understanding of data warehousing concepts (Snowflake, BigQuery, Redshift)
Key Metrics You'll Impact
- Revenue growth
- Conversion rate
- Customer retention
- LTV (Lifetime Value)
- ARPU (Average Revenue Per User)
