Digital planning products play a central role in how we translate demand signals, operational constraints, and network decisions into executable supply chain plans. Our Supply Chain Capabilities organization develops and scales advanced Demand, Supply, Deployment, Network Optimization, and Transportation Planning tools that power decision-making across the end-to-end supply chain.
We are hiring a Product Data Analyst to embed with our product and engineering teams and help ensure these platforms are grounded in high-quality data, robust metrics, and actionable insights. This role sits at the intersection of supply chain domain expertise, analytics, and modern data platforms, supporting both product discovery and delivery at scale.
About the Role
As a Product Data Analyst supporting supply chain planning products, you will be a core member of empowered, cross-functional teams partnering with Product Managers, Solution Architects, Engineers, and Data Engineers. You will help teams deeply understand how planning data flows from source systems into analytical and optimization engines, how users interact with planning outputs, and how product changes translate into measurable business outcomes.
You will own analysis, validation, and measurement across planning products—ensuring insights are timely, accurate, decision-ready, and grounded in real operational behavior. Your work will directly influence roadmap prioritization, solution design, and adoption of planning tools into execution systems.
Responsibilities
Supply Chain Product Analytics & Insight
- Develop deep understanding of demand, supply, inventory, deployment, transportation, and network data and how it is represented across planning products
- Analyze planning results, scenarios, and user workflows to identify gaps, constraints, and improvement opportunities
- Support product discovery by translating complex operational questions into structured analyses and insights
- Partner with Product Managers to evaluate value realization from planning capabilities (e.g., service, inventory, cost, utilization)
Measurement, Metrics & Value Realization
- Define and maintain product and outcome-based metrics tied to planning performance, adoption, and decision quality
- Establish KPIs that connect planning outputs to downstream execution and business outcomes
- Support pilots, releases, and enhancements by measuring impact before and after deployment
- Help teams move from solution delivery metrics to decision and outcome-based measurement
Data Validation, Instrumentation & Quality
- Partner with engineering and data teams to ensure supply chain data is accurate, complete, and fit-for-purpose
- Validate inbound data from enterprise source systems and outbound planning results used by downstream consumers
- Document metric definitions, grain, assumptions, and data lineage across planning domains
- Support root cause analysis for data issues impacting planning results or user trust
Advanced Analytics & Enablement
- Build reusable analyses, dashboards, and exploratory notebooks that support product teams and stakeholders
- Use SQL and PySpark to analyze large, complex planning datasets across multiple domains
- Create clear narratives and visualizations to explain trade-offs, scenarios, and recommendations
- Contribute to raising analytical and data fluency across product and business partners
Data Platforms & Tools
This role works heavily with modern, cloud-based data platforms and CI/CD-enabled analytics workflows, including:
- Microsoft Azure Synapse Analytics and Microsoft Fabric (Lakehouse, Data Warehouse, Semantic Models)
- PySpark Notebooks for large-scale data exploration, transformation, and validation
- Microsoft Azure Pipelines for analytics and data workflow CI/CD
- SQL-based analytics across curated and raw data layers
- Visualization and reporting tools (e.g., Power BI or equivalent)
- SAP S/4HANA (e.g., demand, supply, inventory, production orders, procurement, master data)
- Oracle Transportation Management (OTM) for shipment, rate, and execution data
- Supply planning, network optimization, and transportation planning systems
Key Qualifications
- Bachelor’s degree in analytics, supply chain, industrial engineering, computer science, economics, or related quantitative field (or equivalent practical experience)
- 2-5 years of experience in data analysis, product analytics, or decision support, preferably in supply chain or operations environments
- Strong proficiency in SQL and experience working with large, complex, multi-source datasets
- Hands-on experience with PySpark or distributed data processing frameworks
- Demonstrated experience analyzing supply chain data (demand, supply, inventory, transportation, or network models)
- Ability to connect analytical results to business decisions and product priorities
- Strong collaboration skills in cross-functional, product teams
Preferred Qualifications