Turn day-to-day business questions (SKU performance, sales trends, funnel drop-off, inventory/demand signals) into SQL-driven analysis in BigQuery

Build and maintain ETL/automation pipelines (Airflow/Composer, scheduled BQ jobs, Google Sheets syncs)

Design and productionize dashboards and visualizations for non-technical stakeholders

Apply statistical/ML methods where useful — forecasting (Prophet/XGBoost), cohort analysis, anomaly detection — not just reporting

Partner directly with Supply Chain, Product, and Sales leads to scope requests

Write clean, documented SQL and Python; care about query cost/performance Skills:

2–4 yrs in analytics engineering / data analytics, ideally D2C, e-commerce, or retail

Robust SQL (window functions, CTEs, query optimization) — BigQuery specifically is a big plus

Python for data manipulation (pandas) and automation/scripting

Comfortable working with messy, real-world business data and translating vague requests into structured analysis

Basic statistics/ML exposure (regression, time-series forecasting, hypothesis testing)

📌 Senior Data Analyst (Mumbai)
🏢 Pilgrim
📍 Mumbai