Senior Data Analyst

About the Role

We are looking for an experienced Business Data Analyst to join our Marketplace department. In this role, you will be the analytical partner for teams that manage our marketplace ecosystem, including sellers, buyers, assortment, pricing, and commercial performance. You will turn business questions into well-structured analyses, build reliable dashboards and data models, and deliver insights that directly shape decisions on growth, seller performance, and customer experience.

This position is ideal for someone who combines strong technical skills in SQL, Python, and Power BI with solid statistical knowledge and business sense, and who enjoys owning analyses end to end, from defining the right metrics to presenting clear, actionable recommendations to managers. You will also play a key role in keeping KPIs consistent across teams and in supporting the growth of junior analysts.

Key Responsibilities

• Translate business questions from stakeholder teams into clear analytical problems, with well-defined scope, KPI definitions, and acceptance criteria.
• Design and deliver end-to-end analyses, from data extraction and preparation to insights and recommendations.
• Build and maintain Power BI dashboards and data models that teams rely on for regular performance tracking.
• Write complex, optimized SQL queries and prepare reliable datasets for reporting and analysis.
• Use Python for data processing, statistical analysis, and automation of recurring reports and checks.
• Perform quantitative analyses such as trend and root-cause analysis, segmentation, forecasting, and A/B test evaluation.
• Ensure the accuracy of analytical outputs through validation and reconciliation against reference sources.
• Document KPI definitions, calculation logic, and data sources to keep metrics consistent across teams.
• Present findings to managers in a clear, concise, and actionable way.
• Support and mentor junior analysts through reviews of queries, dashboards, and analyses.

Required Skills & Tools

• SQL (intermediate to advanced): complex joins, CTEs, window functions, and query performance optimization (SQL Server preferred).
• Python (intermediate to advanced): pandas and NumPy for data manipulation, statistical libraries, and scripting for automation.
• Power BI (intermediate to advanced): data modeling (star schema), DAX, Power Query, row-level security, and dashboard design best practices.
• AI (intermediate to advanced):
  • Using LLM tools (e.g., ChatGPT, Claude, Copilot) in daily analytical work, including prompt design and critical validation of AI outputs.
  • Understanding of core machine learning concepts such as regression, classification, and clustering.
• Analytical and mathematical skills:
  • Strong foundation in statistics: hypothesis testing, distributions, regression, and confidence intervals.
  • Strong numerical reasoning and the ability to design accurate calculation logic for complex metrics.
• Nice to have: experience with SSAS/data cubes, ETL tools (e.g., SSIS, dbt, Airflow), or cloud data platforms.

Core Competencies

• Analytical Thinking: Breaks down complex, ambiguous problems into structured, testable questions and draws sound conclusions from data.
• Business Acumen: Understands marketplace dynamics (sellers, buyers, conversion, GMV, pricing, and commission models) and connects analyses to business impact.
• Accuracy & Data Quality Mindset: Takes responsibility for the correctness of every number delivered and proactively validates data and logic.
• Communication & Data Storytelling: Explains insights clearly and persuasively, tailoring the message to both technical and non-technical audiences.
• Stakeholder Management: Builds trusted relationships with business teams, manages expectations, and aligns on priorities and definitions.
• Ownership & Accountability: Drives work from request to delivery and follows up to make sure insights lead to action.
• Prioritization & Time Management: Balances multiple projects and deadlines while focusing on the highest-impact work.
• Collaboration & Mentorship: Shares knowledge generously, gives constructive feedback, and helps raise the team’s overall quality bar.
• Continuous Learning: Stays curious, keeps up with new tools and methods (including AI), and continuously improves ways of working.

Candidate Profile

• 4+ years of experience as a data analyst, preferably in e-commerce, retail, or fast-paced digital businesses.
• Structured problem-solving approach with strong attention to detail and data accuracy.
• Ability to turn business needs into measurable metrics and data-driven solutions.
• Clear communication and data storytelling skills with both technical and non-technical stakeholders.
• Ability to manage multiple projects and prioritize workload effectively.
• Strong ownership, curiosity, and willingness to learn and continuously improve.