Data Analyst

About This Position

We are looking for a Data Analyst to support the Demand Planning team in improving demand forecast accuracy and reliability. You will analyze sales and demand patterns, develop forecasting logic, and build automated tools and monitoring to support inventory and fulfillment decisions, ensuring customer demand is met just-in-time.

If you enjoy turning data into practical forecasting solutions and working cross-functionally to improve product availability, we would love to meet you.

Key Responsibilities

• Demand Forecasting & Business Analysis
  • Analyze demand patterns across SKU, hub, category, time period, campaign, price changes, and seasonal/festive events.
  • Develop, evaluate, and improve demand forecasting logic, including baseline normalization, seasonality, festive events
  • Monitor and analyze forecast-performance metrics
  • Identify and investigate sales and demand anomalies, including unusual spikes or drops caused by festive events, trends, pricing changes, or operational disruption.
  • Translate analytical findings into clear recommendations for Demand Planners and Supply Chain stakeholders.
• Forecasting Logic, Automation & Data Products
  • Translate Demand Planning business requirements into scalable data solutions, including datasets, forecasting logic, dashboards, alerts, and automated workflows.
  • Build and maintain data models and pipelines supporting demand forecasting processes, including data preparation, normalization, imputation, reporting, and configuration management.
  • Automate manual forecasting and monitoring processes using SQL, Python, BigQuery, workflow orchestration/DAGs, and integrations with Google Sheets or reporting tools.
  • Develop alerts and trackers to enable timely responses to changes in demand, pricing, anomalies, campaign performance, and availability risk.
  • Maintain clear documentation for technical logic, data lineage, source tables, configurations, business rules, and operational runbooks.
• Production Pipeline Ownership & Reliability
  • Ensure the reliability and timeliness of daily forecasting pipelines and report-refresh processes.
  • Conduct troubleshooting, root-cause analysis, and remediation for data-quality issues, pipeline failures, reporting discrepancies, and forecast anomalies.
  • Perform manual runs or backfills when required, ensuring workflow sequence and dependencies are executed correctly.
  • Work with Data Engineering, Data Science, and Product teams to improve the robustness, scalability, and maintainability of forecasting systems.

Must Have

• Minimum 1–3 years of experience as a Data Analyst, Business Intelligence Analyst, Analytics Engineer, Supply Chain Analyst, or in a similar role.
• Strong SQL skills and experience working with large-scale datasets, preferably in BigQuery or another cloud data warehouse.
• Proficiency in Python for data analysis, automation, and/or pipeline development.
• Understanding of demand forecasting concepts and evaluation metrics, including baseline, seasonality, outliers, trends, and forecast accuracy metrics.
• Experience building dashboards, automated reports, data pipelines, monitoring tools, or alerts.
• Strong problem-solving, root-cause analysis, and data-validation skills.
• Ability to communicate technical analysis and insights clearly to non-technical business stakeholders.
• High ownership, strong attention to detail, and ability to work effectively in a fast-paced environment with multiple dependencies.

Preferred Qualifications

• Having backgrounds in e-commerce, retail, quick commerce, FMCG, or supply chain related fields.
• Familiar with Airflow/Composer, Git, Google Data Studio, Apache Superset, Google Cloud Platform, or similar tools.
• Exposure to machine-learning forecasting workflows or collaboration with Data Science teams.
• Experience operating and maintaining production data pipelines, including incident handling and backfill processes.