From our roots at the counter of a local Atlanta pharmacy, to our current portfolio of more than 200 beverages, The Coca-Cola Company is one of the most globally-recognized brands in the world. Today, our lineup features beloved beverage brands, including ​
Coca-Cola, Sprite, Fanta, smartwater, Dasani, Topo Chico, BODYARMOR, Powerade, Costa, Georgia, Goldpeak, Minute Maid, Simply, fairlife and more. ​

The Coca-Cola Company is committed to bringing about real change – to our industry, to our local economies, and to the world around us. Through constant evolution, we continue to reimagine the way we refresh the world and make a difference.​

We're innovating our portfolio with products that give people more varieties that meet our consumers where they are. ​

We're working with global partners to transform our business, and grow it in more sustainable ways. ​

And we're providing jobs and opportunities to the local economies where our people live and work, employing 700,000 people throughout our global system alongside bottling partners.​

If you're a changemaker looking to make a change, come join us in our mission to refresh the world and make a difference.​

Position Overview:

The Coca-Cola Company is seeking a Manager, Data Analyst (Data Solutions) to support the Data Analytics & Engineering team within the Digital & Data NAOU organization.

This role serves as a critical bridge between business stakeholders and technical teams, enabling the design and delivery of scalable, high-quality data and AI solutions. The position is responsible for gathering and translating business requirements, and partnering closely with Data Engineering and Analytics Engineering teams to ensure those requirements are accurately implemented as governed data set or data product.

The ideal candidate brings strong analytical and problem-solving skills, a solid understanding of data structures, usage of LLM models for data, and semantic models, and hands-on experience building reports and dashboards using curated datasets (e.g., Power BI). This role plays a key part in ensuring data solutions are aligned to business intent, validated for accuracy, and deliver actionable insights.

Function Related Activities/Key Responsibilities:

Translate business needs into clear functional and technical requirements, working closely with Data Engineers and Analytics Engineers

Collaborate with Data Engineers, Architects, and Solution Owners to design and deliver scalable, high-quality data solutions

Contribute to conceptual and logical data design discussions, ensuring business requirements are accurately reflected in data models

Use SQL, Python, and related tools to perform data exploration, validation, and reconciliation across complex datasets

Create AI data agents leveraging our data foundation as base technology stack such Microsoft foundry & fabric

Define and execute business-aligned data validation and QA/testing strategies across ingestion, transformation, and reporting layers

Identify and resolve data quality, integrity, and consistency issues across systems

Develop and maintain documentation such as source-to-target mappings, business rules, data flows, and data lineage

Build reports and dashboards using curated datasets and existing semantic models, ensuring standardized and governed KPI usage

Partner with Analytics Engineering teams to ensure reporting is built on trusted, scalable, and well-defined data assets

Support data governance and quality practices, including metadata, data definitions, and access controls

Conduct descriptive and diagnostic analysis to support data validation, business insights, and product decision

Education Requirements:

Bachelor’s degree in Computer Science Engineering, Business, Information Systems, Finance, or a related field

Related Work Experience:

Strong experience gathering requirements and translating business needs into data and analytics solutions

Hands-on experience building reports and dashboards using Power BI, Tableau, or similar tools

Experience in data structures, relational data concepts, and semantic data models

Proven ability to collaborate across business, engineering, and architecture teams

Experience in AI architecture for enabling and building AI agents on enterprise data models using Agentic AI frameworks.

Functional and Technical:

Proficiency in SQL and/or Python with ability to work across large, complex datasets

Strong analytical and problem-solving skills with attention to data quality and accuracy

Familiarity with ETL/ELT processes, data pipelines, and modern data platforms (e.g., Azure, Microsoft Fabric, Databricks)

Proficient in creating AI agents that can converse with data models leveraging Agentic AI frameworks and LLM models

Excellent communication skills with ability to work independently while driving across cross-functional teams

Preferred Experience:

Expereince working in CPG domain or beverage sector

Experience working with data lake / data warehouse / lakehouse architectures

Exposure to enterprise data governance and data quality frameworks

Familiarity with data validation, testing, or reconciliation processes

Experience working in enterprise-scale data environments with multiple source systems