About Pandora
Pandora is the world's largest jewellery brand, specialising in the design, crafting and marketing of accessible luxury jewellery made from high-quality materials. Each piece is created to inspire self-expression, allowing people to share their stories and passions through meaningful jewellery. Pandora jewellery is sold in more than 100 countries through 6,800 points of sale, including more than 2,700 concept stores.
Headquartered in Copenhagen, Denmark, Pandora employs 37,000 people worldwide and crafts its jewellery using only recycled silver and gold. Pandora is committed to leadership in sustainability and has set out to halve greenhouse gas emissions across its value chain by 2030. Pandora is listed on the Nasdaq Copenhagen stock exchange and generated revenue of DKK 31.7 billion (EUR 4.2 billion) in 2024.
About Pandora Production Vietnam
Pandora’s new jewellery crafting facility is located in the Vietnam–Singapore Industrial Park III (VSIP III), about 40 km north of Ho Chi Minh City. When fully scaled, the state-of-the-art facility will produce up to 60 million jewellery pieces annually and employ around 7,000 craftspeople. It is powered entirely by renewable energy and built to LEED Gold certification standards.
About the role
The Business Data Analyst turns operational data into practical insights that help the plant reduce downtime, improve yield/quality, and run to plan. Working within Manufacturing Excellence and partnering day‑to‑day with Production, Engineering, and Quality, the role executes discrete analysis and reporting tasks: extracting data (especially from SAP), building and maintaining Power BI/Excel/Tableau dashboards, and delivering clear, actionable summaries for supervisors and managers. The analyst applies straightforward requirement‑gathering techniques, documents KPI logic, and follows agile ways of working to deliver increments reliably. While deep coding is not expected, comfort with data prep, basic SQL, and growing Power BI/DAX skills is important; light Python familiarity is a plus. The role reports to the Senior Manager, Manufacturing Excellence and focuses on execution, quality, and adoption rather than advanced modeling
Key accountabilities:
- Elicit and clarify reporting/analysis requirements via interviews, quick workshops, and doc reviews; translate requests into structured user stories or requirement notes.
- Maintain alignment on objectives/scope; surface trade‑offs early and manage basic change requests with the stakeholders
- Extract and prepare datasets from enterprise systems—especially SAP—plus spreadsheets and local sources; perform cleaning, joins, and basic checks for completeness/consistency.
- Build and maintain Power BI, Excel (incl. Power Query & pivots), and Tableau dashboards/reports to answer recurring questions and track KPIs.
- Perform ad‑hoc analysis (e.g., pareto, trend, variance, root‑cause slices) and summarize implications in plain language with clear visuals.
- Use production/quality data to spotlight opportunities in downtime, yield, scrap/rework, and cycle times; link findings to OEE levers (Availability, Performance, Quality).
- Provide simple, actionable recommendations that supervisors/engineers can trial within the shift or next sprint.
- Validate that dashboards/analyses answer the original questions; run sanity checks against source records and stakeholder expectations before release.
- Log small enhancement requests, prioritize with the lead, and retest before publishing updates.
- Apply basic data quality practices (accuracy, completeness, timeliness); raise issues to data owners/stewards; document logic, filters, and KPI definitions use.
- Provide quick reference guides / short walk‑throughs so end users can self‑serve; capture FAQs to reduce rework and support adoption.
- Work closely with Production Excellence, Engineering, and Quality to ensure analyses reflect real operations and constraints; escalate complex modelling requests to senior analysts/data scientists when needed
Job Requirements
- Bachelor's degree and above in Business Analytics, Mathematics, Operations Research, Industrial Engineering, Mechanical Engineering or related field or an equally strong analytical background.
- Power BI, Excel (advanced functions, Pivot Tables, Power Query), and Tableau for visualization/reporting.
- Familiarity with SAP data structures and extracting/transforming SAP data for analysis.
- SQL (basic querying) for joins/filters/aggregations; Python familiarity is a plus (not required) for light data prep.
- Understanding of DAX for Power BI measures and models is advantageous
- Breaks ambiguous requests into clear, answerable questions; verifies causes vs. correlations.
- Crafts concise narratives with visuals to drive action among non‑technical stakeholders.
- Clarifies expectations, confirms definitions, and manages small changes calmly.
- Attention to detail & quality orientation — checks numbers, filters, joins, and KPIs before sharing; keeps light documentation.
- Understands OEE, downtime categories, and yield/quality drivers to make insights practical.
- Delivers on time and to commitments; raises risks early.
- Comfortable expanding toolset (e.g., DAX in Power BI; basic SQL) to improve throughput over time.
- Seeks feedback, hands off cleanly to seniors for advanced methods when appropriate.
