Kariérní příležitosti

Merchandising Applications Analyst, IBP

Ref #:

W172943

Department:

Information Technology

City:

Cheung Sha Wan

State/Province:

Kowloon

Location:

Hong Kong

Pay Range Max

Pay Range Min

Company Description

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands.

At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

Position Overview

The Merchandising Applications Analyst, IBP supports APAC merchandising planning by bridging business and IT teams across regions. The role focuses on requirement gathering, data validation, and UAT execution for the IBP (o9) program across Demand Planning, MFP/LFP, Assortment, and Location Planning. The Analyst owns key APAC deliverables—such as the delta/decision log, requirements pack, data validation pack, UAT pack, and reporting/KPI documentation—and coordinates decisions and alignment across business, delivery, and data/analytics teams.

Essential Duties & Responsibilities

  • Gather and document business and technical requirements with clear acceptance criteria
  • Translate needs into BRD / functional specs (as required), use cases, and user stories
  • Maintain an APAC delta/decision log (owner, due date, impact) and escalate blockers
  • Document source-to-target mappings for key integrations (source fields, transformations, target fields)
  • Define and execute data validation/reconciliation checks (counts, totals, hierarchy completeness) and manage exceptions with owners
  • Support phase-based readiness checkpoints aligned to the IBP program (e.g., blueprint/interface freeze, SIT/UAT)
  • Coordinate actions, dependencies, and follow-ups across stakeholders via backlog/defect discipline (Jira/Confluence)
  • Facilitate working sessions with cross-functional and cross-regional teams to confirm scope, sequencing, deltas, and readiness
  • Consolidate feedback into actionable backlog items/defects with clear severity and business impact
  • Maintain Jira/Confluence as the source of truth (requirements, decisions, backlog, defects, release/impact notes)
  • Capture reporting/KPI requirements for IBP outputs (definitions, dimensions, drill paths)
  • Produce lightweight wireframes/prototypes (Power BI/Excel/PPT) to validate KPI definitions and user workflows; maintain a KPI glossary
  • Identify opportunities to improve requirement traceability, test efficiency, and data reconciliation/monitoring
  • Apply internal standards and best practices for BA delivery (documentation, testing, change control)

Experience, Skills & Knowledge

  • 3–5 years of experience as an IT Business Analyst (generalist BA background is acceptable)
  • Strong analytical thinking, structured documentation skills, and exceptional attention to detail
  • Solid data literacy: able to reason through SQL-level logic, understand source‑to‑target mappings, and perform reconciliation checks; Excel proficiency is helpful
  • Proficient in Jira and Confluence, with the ability to collaborate effectively across time zone
  • Exposure to IBP/o9 or related retail planning domains (e.g., demand planning, MFP/LFP, assortment, location planning)
  • Experience in retail or fashion; understanding of planning hierarchies and foundational master data concepts