Director, Supply Chain Lead Product Data Analyst

Coca-Cola•Atlanta, GA

About The Position

The Coca-Cola Company is hiring a Director-level Lead Product Data Analyst for its North America Operating Unit Supply Chain Digital Enablement Team. The role is embedded in cross-functional product teams and partners with Product Managers, Data Architects, Data Engineers, Product Designers, and business stakeholders to turn complex supply chain data into trusted insights and scalable data products. The analyst works autonomously in complex and ambiguous problem spaces, helping teams understand performance, evaluate opportunities, and measure outcomes across the end-to-end supply chain. The role leads sophisticated analyses, shapes data models and metrics, and informs prioritization and trade-offs with evidence. It also helps strengthen analytical standards, measurement discipline, and self-service insight across product teams and stakeholders. The work spans procurement, manufacturing, inventory, transportation, planning, and customer fulfillment, and includes developing decision-ready reporting and products from multi-source operational data. The position uses Microsoft Azure Synapse Analytics and Microsoft Fabric, PySpark notebooks, Azure Pipelines, SQL, and visualization and reporting tools such as Power BI. The role is based in Atlanta, United States, with 0%–25% travel and relocation provided. The stated U.S. base pay range is $164,000–$193,000, with an annual incentive reference value of 30%. The company does not offer employment-visa sponsorship; applicants must be authorized to work full-time in the United States without requiring sponsorship.

Requirements

Bachelor’s degree in analytics, statistics, economics, computer science, industrial engineering, supply chain, or a related quantitative field, or equivalent practical experience.
At least 7 years of experience in data analysis, analytics, or business intelligence supporting complex operational or supply chain domains.
Advanced SQL querying skills and mastery of Python or another scripting language, including PySpark.
Extensive experience with supply chain data from systems such as SAP S/4HANA, Oracle Transportation Management (OTM), Manufacturing Execution Systems (MES), and other supply chain systems.
Experience with statistical methods and modeling techniques, and working knowledge of machine learning models.
Experience with data quality assessment, validation, and root cause investigation.
Proven ability to influence decisions through data and clear communication.
Strong collaboration skills and experience working in cross-functional product or platform teams.
Ability to work independently and foster a data-driven culture of growth.
Currently authorized to work full-time in the United States without requiring The Coca-Cola Company’s employment sponsorship.

Nice To Haves

Master’s degree in a related quantitative or supply chain field.
Experience supporting enterprise-scale supply chain data platforms or analytics products.
Experience applying forecasting and optimization modeling to supply chain planning, execution, or operational decision-making.
Knowledge of Azure and Microsoft Fabric storage and compute concepts that support scalable analytics products.

Responsibilities

Develop a deep understanding of end-to-end supply chain processes and data, including procurement, manufacturing, inventory, transportation, and customer fulfillment.
Analyze large, complex datasets to identify performance drivers, risks, trade-offs, and improvement opportunities across planning and execution.
Translate operational and optimization data into actionable insights that inform product strategy, roadmap decisions, and business priorities.
Explain why performance outcomes occurred and recommend actions, while proactively surfacing high-value opportunities.
Informally mentor analysts and partners through collaboration, review, and shared best practices.
Partner with Product Managers and stakeholders to define product objectives, success metrics, KPIs, and outcome-based measures.
Design, maintain, and document analytical models, metrics, and business logic that support scalable data products and decision intelligence.
Support the shift from static reporting toward reusable, trusted data assets and analytical products.
Advise on the appropriate level of analytical rigor based on decision risk, business value, and operational impact.
Work with data architects and data engineers to define, validate, and evolve data models in Microsoft Azure.
Ensure analytical outputs are accurate, reliable, and aligned with supply chain process realities.
Steward data quality, metric definitions, and analytical assumptions across products.
Document data logic, metrics, and methodologies to support transparency, reuse, and auditability.
Create dashboards, analytical views, and narratives that make complex supply chain data accessible and actionable.
Communicate insights clearly to technical and non-technical audiences, including supply chain leaders.
Raise analytical fluency and contribute to a data-informed culture across supply chain product teams.
Collaborate with analysts, data architects, data engineers, and data scientists to align insights across domains.