Materials Planning Operations Lead

Job Title: Materials Planning Operations Lead

Location: Beaverton, OR

Duration: 12 months

Pay Range: $(44.36– 46.67)/hr on W2 all-inclusive without benefits

Job Description:

• Expected contract length: 12 months from start date
• Team details & who they will work with: Process and operations for footwear and apparel Materials, accessories forecast

Desired Candidate Profile:

• Minimum required years of experience: 5 YOE Data Analyst with Supply chain experience
• Education requirements: Bachelor’s degree or equivalent experience

Top must-have skills include the following:

• Reporting for Supply chain materials planning
• Excel
• Comfortable taking business processes and leading improvement initiatives

Nice to have skills:

• Understands SQL and Databricks, can tell if Ai is hallucinating dashboards/reports
• Independent working, ambiguous environment,

Software/technical requirements:

• Using Ai tools to make dashboards and reports
• Previous Client/industry experience preference: yes

Who We're Looking For

• The Materials Planning Operations Lead owns the vision and delivery of scalable tools, automated workflows, and executive-ready reporting for Client's global materials sourcing and planning functions.
• You combine deep technical fluency in modern data platforms and AI-assisted development with a continuous improvement mindset, strong product thinking, and the ability to influence senior stakeholders through clarity, rigor, and compelling narrative.

Qualifications:

• Bachelor's or Master's degree in Business, Data Science, Supply Chain, Engineering, or a related field; will accept any suitable combination of education, experience, and training
• Minimum of 5 years of experience in data analytics, analytics engineering, process improvement, or supply chain operations, with demonstrated lead or senior IC scope (owning roadmaps, standards, or cross-team initiatives)
• Expert-level proficiency in SQL for data querying, manipulation, and pipeline development; strong Python for automation, data modeling, and application logic
• Hands-on experience building and operating production analytics experiences in Databricks, including Databricks Apps for interactive reporting, operational dashboards, and stakeholder-facing tools
• Proven ability to use AI-powered development environments (including Cursor and GitHub Copilot) to design, build, and maintain business automation, analytical pipelines, and world-class reporting with high velocity and quality; you treat AI-assisted engineering as a core competency, not a novelty
• Comfort working in Git-based collaboration (e.g., GitHub) for version control, code review, and repeatable deployment of analytics and automation assets
• Track record of translating complex, multi-dimensional supply chain data into clear, actionable narratives and leadership-ready materials for both technical and non-technical audiences
• Experience leading process improvement or transformation initiatives end-to-end: discovery, design, implementation, change management, and adoption measurement
• Experience in materials planning, strategic sourcing, or supply chain analytics is strongly preferred

What You Will Work On:

• As the Materials Planning Operations Lead, you will be the conduit between enterprise data, automated execution, and meaningful business action.
• You will define how Materials Sourcing and Planning teams see performance, run operations, and scale capability.
• You will set the reporting and automation strategy for Materials Operations Excellence: prioritize the backlog, establish standards for data quality, documentation, and reusable patterns, and align deliverables to Materials Planning leadership priorities.
• You will design, build, and operate world-class reporting and decision-support experiences using Databricks Apps and related platform capabilities—delivering real-time visibility into KPIs, trends, scenarios, and performance opportunities with a product-minded focus on usability and adoption.
• You will architect and automate end-to-end data workflows that reduce manual effort, improve reliability, and increase speed-to-insight across the materials organization; own critical pipelines from requirements through production support.
• You will leverage SQL, Python, and Databricks to query, transform, and model large-scale supply chain datasets, enabling scalable, governed, and repeatable analytics.
• You will lead with AI-assisted development: use Cursor and GitHub Copilot to rapidly prototype, harden, and maintain automation (scheduled jobs, integrations, self-service tools, and reporting logic), raising the bar for code quality, testing discipline, and maintainability across the team's deliverables.
• You will identify, design, and lead high-impact process improvement initiatives in partnership with Materials Planning stakeholders—translating operational pain points into durable technical solutions and measurable outcomes.
• You will craft executive-ready data stories for senior leadership, applying best-in-class visualization, narrative structure, and decision framing to drive alignment and action.
• You will serve as the senior subject matter expert for the Materials Operations Excellence toolset—owning technical standards, documentation, and delivery of modern analytics, automation, and AI-assisted engineering solutions for sourcing and planning.

Who You will work with

• As the Materials Planning Operations Lead, this role reports to the Manager, Materials Operations Excellence and serves as the senior analytical and technical leader for the materials organization.
• You will set direction for reporting, automation, and data products while partnering with Client's Materials Planning leadership and IC community as a trusted advisor on how to scale insight and execution.
• You will collaborate across Supply Chain, Technology, and Operations to define standards, prioritize the roadmap, and deliver enterprise-grade reporting solutions, intelligent automation, and process transformation that drive measurable efficiency and business impact at scale.