Senior Business Analyst (6 months contract)
About the Role
The engagement is structured across two phases:
| Phase | Timeframe | Focus |
| Phase 1 | Month 1 | WMS Impact Assessment — inventory of impacted assets, pipeline analysis, risk identification, parallel run design, KPI impact review, effort estimation |
| Phase 2 | Months 2–6 | Broader Data & Analytics Stream — data mapping, Data quality uplift, pipeline development, reporting uplift, and ongoing analytics delivery across the enterprise reporting environment |
This role is pivotal in ensuring the analytics function can anticipate, plan for, and support the complexities of the WMS transition — including a parallel run period where both legacy and new platforms will be operating concurrently, feeding the enterprise reporting environment simultaneously.
Required Experience & Skills
B2C Retail & Supply Chain Analytics
- Demonstrated experience working within or alongside B2C retail businesses, with strong familiarity with retail operations, supply chain, and DC processes
- Hands-on understanding of retail KPIs — particularly inventory management, fulfilment, labour productivity, and financial reporting in a retail context
- Prior exposure to warehouse management systems (WMS) or distribution centre operational data is highly regarded
- Familiarity with the data and reporting implications of DC automation, operational process change, or systems cutover in a retail environment
Technical Analytics Stack
- Strong working knowledge of Snowflake — including schema design, object-level understanding, and ability to assess data model impacts
- Practical experience with dbt (data build tool) — ability to read, interpret, and assess dbt models, lineage graphs, and project structures
- Proficiency in Tableau — able to assess workbook complexity, data source dependencies, and reporting impacts
- Comfortable working with Excel-based reporting and operational processes, including assessing their data dependencies and uplift requirements
Business Analysis Capability
- Strong experience conducting impact assessments and scoping exercises for complex data or technology change programmes
- Able to work at pace to produce structured, actionable outputs without over-engineering — comfort with OOM estimation and assumption-based scoping
- Skilled at stakeholder engagement across technical and non-technical audiences, including senior business stakeholders and analytics engineers
- Experience documenting future-state processes, data flows, and system interactions in the context of technology or operational change
- Familiarity with data programme delivery in an agile or hybrid delivery environment
Desirable
- Experience with WMS platforms (e.g. Manhattan, Blue Yonder, Körber, Infor, or similar)
- Prior involvement in a DC automation, WMS implementation, or major DC operational change
- Exposure to enterprise data strategy, data governance, or analytics centre of excellence environments
- Understanding of parallel run and cutover complexities in the context of data and reporting
Phase 1: WMS Analytics Impact Assessment (Month 1)
Key Activities
- Conduct a systematic, object-level inventory of impacted assets across the analytics stack, spanning dbt models, Snowflake schemas and objects, Tableau workbooks and data sources, and Excel-based operational reports and processes
- Identify and document impacted data pipelines, ingestion patterns, transformation logic, and reporting outputs across DC-related domains
- Assess the analytical implications of transitioning from legacy DC processes and KPIs to those introduced by the new automated WMS environment
- Develop a high-level solution design to support the parallel run period, where both old and new WMS platforms will be live simultaneously — including dual data feeds, reconciliation requirements, and impacts on ingestion, modelling, and reporting layers
- Identify potential showstoppers, critical dependencies, and major risks that could impede analytics delivery during or after cutover
- Produce high-level order-of-magnitude (OOM) delivery effort estimates for the eventual implementation phase, supported by clearly stated assumptions
- Conduct a specific, focused assessment of impacts to DC KPI and executive reporting, with particular attention to:
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- Inventory accuracy, stock on hand, and fulfilment metrics
- Labour productivity and DC operational KPIs
- Financial reporting and cost-per-unit/throughput metrics
- Executive dashboards and summary reporting
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Phase 2: Broader Data & Analytics Delivery (Months 2–6)
Anticipated Activities
- Business analysis and requirements definition for data pipeline and modelling work arising from the a broader business ERP replatform
- Documentation of future-state warehouse processes, system design changes, and operational workflows as they relate to data and analytics requirements
- Support for parallel run analytics delivery, including reconciliation reporting and dual-feed validation
- Ongoing stakeholder engagement across DC Operations, Finance, Merchandise, and Technology to ensure analytics outputs align to business needs
- Contributing to the analytics roadmap, backlog management, and prioritisation within the programme
- Support for UAT, data validation, and cutover readiness activities from an analytics perspective
