Data Analyst (Supply Chain / Quality)

About the Role

We are supporting a leading global retailer’s Asian sourcing hub in hiring an autonomous, self-driven Analytics Engineer to own data excellence across Quality, Packaging, Responsible Sourcing (CSR/ESG), and Costing.

This role bridges operational realities with executive strategy by engineering robust data pipelines, establishing a Single Source of Truth, and building interactive Control Tower dashboards that turn raw data into high-impact business decisions.

Key Responsibilities

• Data inventory & profiling: Audit, map, and document existing metrics/KPIs and data sources; define the department “Single Source of Truth” within the first 90 days.
• Requirements & translation: Partner with stakeholders across Quality, Packaging, Responsible Sourcing and Costing to translate operational needs into clear reporting definitions and business requirements.
• Pipeline enablement: Collaborate with the Digital/Tech team to automate and standardize data pipelines, reducing manual extraction and improving refresh reliability.
• Data quality & governance: Implement quality controls, validation checks, and “clean at the source” practices; provide light training/guidance to operational users and external partners.
• Insights & recommendations: Analyze datasets to identify trends and risks; deliver actionable process improvement recommendations on a regular cadence.
• Dashboards / Control Tower: Design and deploy stakeholder-friendly dashboards (Agile iterations), enabling real-time decision-making and measurable adoption.
• Communication & stakeholder management: Present insights and track follow-ups with business owners; act as the bridge between raw data and operational execution.

Requirements

• Bachelor’s degree in Business Analytics, Supply Chain, Data Science, or related discipline.
• Experience: Ideally 5–7 years (minimum 3–4) in analytics/MI/reporting for operations, sourcing, quality, supply chain, compliance, sustainability, or similar.
• Strong stakeholder management and data storytelling skills (comfortable with senior/non-technical audiences).
• Hands-on capability with:
  • Excel / Google Sheets (Power Query / pivots; macros/AppScript a plus)
  • BI tools (Tableau / Looker Studio / Power BI)
  • SQL (BigQuery preferred)
  • Familiarity with modern AI tools is a plus
• Languages: Strong English required; Mandarin/Cantonese/French is a plus.

What Success Looks Like

• Clear, documented KPI definitions and an agreed “Single Source of Truth.”
• Reduced manual reporting effort through automation.
• Reliable dashboards with stakeholder adoption and measurable business impact.