Warehouse Data Analytics Specialist - Bukit Raja, Klang

Shopee; Kuala Lumpur; On-site; MYR 54,000 - 102,000; Full time

Job summary

Shopee is seeking a data analyst to support warehouse operations through daily data analysis and SQL-driven reporting. The role involves collaborating with product teams to improve processes and drive data-informed decisions across inbound, inventory, and outbound flows.

The candidate will work with cross-functional teams, handle multiple requests, and contribute to capacity planning and operational projections for warehouse expansion.

Qualifications

• Bachelor's degree in a relevant field is required.
• Strong analytical and problem-solving abilities.
• Experience handling large datasets and multiple requests.
• Excellent communication with diverse stakeholders.

Responsibilities

• Perform daily data analysis to support inbound, inventory and outbound warehouse operations.
• Write and optimize SQL queries to retrieve, process, and analyze large datasets.
• Manage and fulfill internal data and project requests independently.
• Collaborate closely with product teams to support product improvement initiatives using data-driven insights (e.g., identifying process delays, system errors).
• Support warehouse expansion and automation projects by conducting capacity studies, headcount forecasting, and operational projections.
• Work with cross-functional teams to ensure data accuracy and support business objectives.

Skills

SQL

Analytical thinking

Communication

Education

Bachelor's degree in Data Analytics, Statistics, Computer Science, Engineering, or related fields

Tools

SQL

Job description

Shopee is seeking a data analyst to support warehouse operations through daily data analysis and SQL-driven reporting. The role involves collaborating with product teams to improve processes and drive data-informed decisions across inbound, inventory, and outbound flows.

The candidate will work with cross-functional teams, handle multiple requests, and contribute to capacity planning and operational projections for warehouse expansion.