Senior Data Analyst

About the opportunity As a Senior Data Analyst in the Quick Commerce & Partnerships Analytics team, you will leverage your expertise to directly impact the quick commerce strategy and growth of our 16 markets by delivering actionable insights and advanced analytics solutions. In this role, you'll work as an embedded thought partner with senior quick commerce stakeholders to influence strategy and tactics, mentor junior analysts, and leverage AI to build the future of quick commerce analytics. This is a high-visibility position that plays a pivotal role in data-driven decision-making. Strategic Analysis: Design and execute robust analytical methodologies including causal impact modeling and measuring incremental ROI on quick commerce investments (examples: dark store expansion, assortment changes, delivery fee adjustments, discounting) and make actionable recommendations on capital allocation and tactical execution of quick commerce initiatives. Stakeholder Engagement & Influence: Collaborate closely with senior quick commerce, operations and supply chain partners to understand strategic objectives, recommend analytics solutions, negotiate priorities, and present insights effectively. Advanced Data Modeling & Measurement: Define measurement frameworks and metric definitions for key quick commerce initiatives (e.g. Shops, dark store performance, fulfillment/delivery metrics); lead the development of complex SQL models to implement as well as transform massive datasets into actionable insights using tools like BigQuery and dbt. Strategic Reporting & Visualization: Design and build compelling, user-friendly data assets including both traditional dashboards (e.g. Looker, Tableau) and agentic solutions (e.g. root-cause analysis agents for delivery delays or stockouts) that facilitate decision-making for business leaders. Mentorship & Development: Provide guidance and mentorship to junior analysts, enhancing their technical skills and fostering a collaborative team environment. AI-Driven Analytics & Automation: Identify, design, and implement AI-powered solutions that transform how quick commerce analytics operates — including agentic workflows (e.g. root-cause analysis agents, automated anomaly detection on delivery/fulfillment metrics), LLM-assisted insight generation, and prompt-engineered pipelines. Translate repeatable analyst workflows into scalable AI tools. Act as a driver of AI adoption within the team, setting standards and upskilling junior analysts.