Manager, Business Intelligence & Analytics - Supply Chain

Company Overview

Why Choose Us?

Novolex is a leading manufacturer of food, beverage, and specialty packaging that supports multiple industries including food service, restaurant delivery and carryout, food processing, grocery and retail, and industrial sectors. Novolex manufacturing and sourcing expertise spans a diverse range of substrates including resin, paper, molded fiber, aluminum and more. We provide customers a broad array of stock and customized solutions with 120 product categories, 250 brands and over 39,000 SKUs.

Our Sustainability Commitment

The Novolex sustainability vision is built upon three pillars: our products, our operations and our people. Each is critically important to our growth and future as a business. These pillars form the foundation of our company-wide commitment to sustainability, helping us achieve our ambitious goals through our wide-ranging initiatives.

Job Description

Role Overview

The Manager, BI & Analytics is responsible for leading the design, development, and governance of data architecture, business intelligence solutions, and analytics platforms that support Sales, Inventory, and Operations Planning (SIOP) process. This role ensures the delivery of scalable, reliable, and consistent data solutions that enable data-driven decision-making across the supply chain organization.

The ideal candidate combines strong technical expertise with business acumen, enabling alignment between strategy, analytics capabilities, and operational objectives.

Key Responsibilities

Data & BI Platform Leadership

* Design, build, and maintain SIOP dashboards, reports, and analytics tools

* Lead the development and optimization of scalable BI platforms (e.g., Power BI, Tableau, etc.)

* Ensure seamless integration of data across multiple enterprise systems

Data Architecture & Engineering

* Manage data models, pipelines, and transformations supporting planning and analytics

* Oversee data architecture to ensure scalability, performance, and maintainability

* Partner with IT and data engineering teams to align infrastructure and tools

Data Quality & Governance

* Establish and enforce data governance frameworks, standards, and best practices

* Ensure accuracy, consistency, and integrity of SIOP data

* Define and maintain standardized metric definitions and business logic

Analytics Enablement

* Enable and promote self-service analytics capabilities for business users

* Translate business requirements into technical solutions and insights

* Support advanced analytics, forecasting, and modeling initiatives

Stakeholder Engagement

* Collaborate with supply chain, finance, and operations leaders to align reporting needs

* Act as a trusted advisor for data-drive decision-making

* Communicate insights and recommendations clearly to both technical and non-technical stakeholders

Team Leadership & Development

* Lead, mentor, and develop BI and data professionals

* Drive a culture of continuous improvement, innovation, and accountability

* Establish priorities and manage workload across multiple initiatives

Qualifications

* Bachelor's degree in information Systems, Data Analytics, Computer Science, or a related field

* 6+ years of experience in business intelligence, data engineering, or analytics

* Proven experience with BI platforms (e.g., Power BI, Tableau, etc.) and data modeling

* Strong understanding of data warehousing, ETL processes, and data pipelines

* Experience implementing data governance practices and frameworks

* Familiarity with supply chain or SIOP processes preferred

Core Competencies

* Data Architecture:
Designing scalable and efficient data ecosystems

* BI Development:
Building intuitive and impactful dashboards and reports

* Data Governance:
Ensuring data integrity, consistency, and compliance

* Dashboard Design:
Translating complex data into actionable insights

* Platform Enablement:
Driving adoption and usability of analytics tools

Success Measures

* High adoption rates of dashboards and analytics tools across the organization

* Improve data accuracy and reduction in reporting discrepancies

* Consistency in KPI definitions and reporting outputs

* Performance and reliability of BI platforms and data pipelines

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