Summary written by USA Jobs 24 from Coca-Cola's advert and our data on 17,030 current US jobs. How we check every job
At a glance
Coca-Cola is hiring a Director, Supply Chain Lead Data Architect in Atlanta, GA. It is a full-time role in Data, AI & Analytics, asking for at least 7 years of experience, first listed on November 4. The description mentions Data modelling, CI/CD, Cybersecurity, Azure, Power BI and Databricks. Coca-Cola has 99 other openings in the US, 52 of them in Atlanta, GA. Across all employers on USA Jobs 24 there are 78 Data & AI openings in Atlanta, GA today; the typical one asks for 7 years and advertises about $194,000 a year at the midpoint.
Data modellingCI/CDCybersecurityAzurePower BIDatabricksAgile
How the pay compares
Coca-Cola has not published pay for this job, or we could not find it in the advert. Of the 94 data & AI jobs in Georgia on USA Jobs 24, 60% show pay, and the typical yearly midpoint among them is $180,000. That gives you a fair starting point when the subject comes up.
Skills in this advert
How often each skill named in this advert appears across the 1,778 data & AI jobs we list today. CI/CD is the most widely requested (11% of jobs), while Power BI is the least common (5%). Widely requested skills are what employers expect as a baseline; rarer ones show what is special about this job.
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Before you apply
- Check it is still open. We found this job on Coca-Cola's Workday site on November 4 and checked it again November 4, 5:17 AM ET. When an employer takes a job down, we remove it at our next daily update.
- Check the location works for you. This role is based in Atlanta, GA. If you would need to move, ask whether relocation help is offered.
- Match the experience. The advert asks for at least 7 years of experience. If you are a little short, a close match on the skills in the advert can still win an interview.
- Tailor your resume. Use the advert's own words, such as Data modelling, CI/CD and Cybersecurity, wherever they are true for you. Our resume guide shows how.
- Apply only through Coca-Cola's own site. Our Apply button goes straight to Coca-Cola's Workday page. If anyone contacts you about this job and asks for money, gift cards or bank details, stop and check it with our scam checker. Read how to spot a fake job offer.
About hiring at Coca-Cola
Coca-Cola has 100 openings on USA Jobs 24 today across 11 states. Most are in operations (23), data & AI (12) and engineering & mfg (12). The biggest locations are Atlanta, GA (53), Auburndale, FL (6) and Draper, UT (5). 19% of them are remote, 5% are open to entry-level candidates and 4% show pay. We collect Coca-Cola's jobs every day straight from its own careers system (Workday), never from job boards or agencies.
The employer's advert
This is Coca-Cola's own description of the job, copied word for word from its careers site. We have not edited it.
Show the full advert from Coca-ColaHide the advert1,377 words
Job Description Summary:
The Supply Chain Lead Data Architect will own the supply chain data model and the data-product architecture that enables trusted analytics, decision intelligence and data science across the North America Operating Unit. This leader will treat data as a product: defining the business purpose, consumers, ownership, quality expectations, access patterns, lifecycle and measurable value of the data assets the organization depends on. The role combines supply-chain domain mastery with enterprise data modeling, platform product strategy and modern engineering fluency. Partnering with supply chain, product, analytics, data science, Global Data and AI, Enterprise Architecture, Security, Governance and platform teams, the successful candidate will translate business decisions into interoperable, secure, governed and reusable data capabilities that improve performance and deliver measurable business value.
This is a Director-level role.
About the Role
Own Supply Chain Data Products and Enterprise Data Models
- Define and execute the supply chain data-product strategy and multi-year architecture roadmap that enables analytics, reporting, decision intelligence and data science.
- Develop and own the canonical supply chain data model, including conceptual, logical and physical models, shared business definitions and semantic layers for domains such as demand, supply, inventory, manufacturing, logistics, customer service and performance.
- Establish reusable patterns for data products, ingestion, integration, lakehouse and warehouse platforms, APIs, events and streaming, master and reference data, semantic models, analytics and data-science consumption.
- Lead architecture reviews and technology decisions, balancing decision value, interoperability, scalability, security, quality, reliability, performance, cost and speed to market.
Enable Integration Interoperability and Modern Data Engineering
- Connect supply chain data requirements with enterprise platforms, applications and standards, reducing duplicate data, fragmented definitions, point-to-point integrations and technical debt.
- Define integration and interoperability standards across ERP, manufacturing, warehouse, transportation, planning, customer and external-partner systems using APIs, events, common identifiers and governed data contracts.
- Set engineering standards for CI/CD, Infrastructure as Code, automated testing, orchestration, observability, metadata, lineage, data quality, reliability and operational support.
- Drive reusable frameworks, platform capabilities and product operating practices that accelerate delivery and make data easy to discover, understand, access and use responsibly.
Improve workload performance, resilience and cost efficiency across cloud data, analytics and data-science platforms.
Translate Business Decisions into Data Requirements
- Work with supply-chain leaders to identify the decisions that matter most, the measures that define success and the data required to improve planning, service, cost, inventory, capacity, resilience and sustainability outcomes.
- Convert business priorities into clear data requirements, data-product backlogs, domain models, data contracts, acceptance criteria and delivery roadmaps that technical teams can execute.
- Define patterns that enable data scientists and analysts to use governed, explainable and fit-for-purpose data, including feature-ready data, semantic models and secure self-service access.
- Partner with data science and engineering teams to move analytical and predictive solutions from prototypes to secure, observable and reliable production capabilities.
- Establish architecture guardrails for privacy, security, governance, model use, explainability, evaluation and appropriate human oversight where AI is applied.
Lead Cross Functional Delivery and Augmented Teams
- Serve as a trusted partner to supply-chain, product, finance, operations, data science and technology leaders; communicate architecture choices, dependencies, tradeoffs, value, cost and risk in clear business language.
- Lead cross-functional teams and augmented resources, setting clear outcomes, architectural guardrails, delivery expectations and quality standards while building capability in internal teams.
- Facilitate alignment across organizational boundaries, resolve design decisions and sequence investments to deliver the highest-value data products first.
- Improve the discoverability, accessibility, quality and usability of trusted supply-chain data so teams can move from questions to decisions more efficiently.
Drive Governance Quality Value and Enterprise Alignment
- Establish data-product governance with clear ownership, stewardship, quality rules, service expectations, metadata, lineage, retention and least-privilege access from design through operations.
- Partner with NAOU Digital and Data, Global Data and AI, Enterprise Architecture, Cybersecurity, Privacy, Governance and platform organizations to align supply-chain solutions with enterprise direction.
- Establish measures and operating reviews for data quality, adoption, reuse, time to insight, delivery speed, reliability, cost, risk reduction and realized supply-chain value.
- Build a high-performing culture focused on accountability, product thinking, value creation, inclusion, quality and continuous improvement; mentor technical talent and augmented team members.
- Enable teams to make decisions within clear architectural guardrails and continuously improve the data-product portfolio based on stakeholder feedback and performance evidence.
What You Will Need
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science or a related field, or equivalent professional experience; advanced degree is a plus.
- 7+ years of progressive experience in data architecture, enterprise data modeling, data engineering or analytics platforms, including leadership of complex enterprise-scale transformations.
- 7+ years of experience leading architects, engineers, technical leaders, augmented resources or multidisciplinary platform teams, including responsibility for talent development and delivery outcomes.
- Demonstrated supply-chain domain expertise and experience translating supply-chain processes and decisions into data requirements, business definitions, data models and analytical products.
- Demonstrated expertise designing enterprise conceptual, logical and physical data models; canonical data models; master and reference data; semantic models; and data products for analytics and data science.
- Demonstrated experience designing cloud-native architectures spanning lakehouse and warehouse platforms, data products, streaming, APIs, events, semantic models and analytical consumption.
- Experience with enterprise cloud data platforms such as Microsoft Azure, Microsoft Fabric, OneLake, Power BI and Azure Databricks, or comparable technologies.
- Strong understanding of integration and interoperability patterns, including APIs, event-driven architecture, data contracts, common identifiers and operational-system integration.
- Strong understanding of CI/CD, DevOps, DataOps, Infrastructure as Code, automated testing, orchestration, observability and cloud cost-management practices.
- Deep understanding of data governance, security, privacy, metadata, lineage, data quality, stewardship, access control and data-product operating practices.
- Demonstrated ability to influence senior business and technology leaders, lead decisions across organizational boundaries, manage augmented resources and communicate complex topics in clear business language.
- Experience translating technology investments into measurable outcomes across data quality, reliability, adoption, reuse, speed, cost, risk and realized business value.
- Proven track record of working independently, applying platform product strategy and fostering a growth mindset culture in a data-product environment.
Skills:
Architecture Development, Business Partnerships, Data Architecture Development, Data Governance, Data Modeling, DataOps, Data Quality, Data Requirements, Decision Making, Emerging Technology Trends and Practice, Enterprise Architecture (EA), Enterprise Cloud, Enterprise Data, Enterprise Data Modeling, Enterprise Platforms, Long Term Planning, Metric Creation, Microsoft Azure, Prioritization, Product Architecture, Strategic Solutions, Technology RoadmapPay Range:
United States: 171,000 - 198,000 USD
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
30Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
YesJob Posting End Date:
November 13, 2026Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.USA Jobs 24 copied this listing from Coca-Cola's official careers site on November 4, 2026 and checked it again November 4, 5:17 AM ET. Coca-Cola will never ask you to pay to apply or to buy equipment with a check they send you. If anyone does, it is a scam.
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