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Job Description Summary:
The NAOU Marketing Data team is responsible for building the data foundation, engineering capabilities, and analytics solutions that enable better marketing decisions across North America. The team connects data, technology, and insights to create scalable capabilities that support consumer understanding, marketing effectiveness, measurement, personalization, and AI-driven decision-making.
Working across Marketing, Integrated Marketing Experience (IMX), Human Sciences, Advanced Analytics, MarTech, Digital Technology, and enterprise data teams, the organization helps transform data into a strategic asset that drives growth, innovation, and business impact.
Role Overview
The Director, Data Engineering will lead the hands-on design, development, and operation of scalable marketing data pipelines and curated data products across Microsoft Azure. The role transforms internal and external data into trusted, governed, reusable assets for analytics, measurement, activation, personalization, and AI-enabled decision-making.
This player-coach will set engineering standards while actively designing solutions, writing and reviewing code, and resolving complex issues. The role partners with Marketing Data Architecture, Marketing Analytics, MarTech, Digital Technology, and enterprise data teams to deliver secure, reliable, observable, and cost-effective capabilities.
What You Will Do for Us
Design & Build Azure Data Pipelines: Personally design, code, test, deploy, and operate scalable batch and streaming pipelines across Azure. Integrate consumer, media, commerce, CRM, loyalty, Adobe, and enterprise data sources using reusable engineering patterns.
Curate Trusted, AI-Ready Data Products: Build standardized, documented datasets and data products that are accurate, discoverable, reusable, and ready for analytics, machine learning, and generative AI. Apply strong data modeling, metadata, lineage, and data contract practices.
Lead Hands-On Engineering & Technical Design: Translate business and architecture requirements into production-grade solutions. Create technical designs, write and review Python, SQL, and PySpark code, troubleshoot complex issues, and balance speed, scale, quality, and maintainability.
Establish GitHub Engineering & DevOps Practices: Use GitHub for source control, pull requests, code reviews, documentation, and collaboration. Implement automated testing, CI/CD, infrastructure as code, release management, and secure development practices.
Use AI-Assisted Development Responsibly: Use Codex, Cursor, and GitHub Copilot to accelerate design, coding, testing, refactoring, and documentation. Establish validation and security guardrails so AI-generated code meets enterprise engineering, privacy, and quality standards.
Ensure Reliability, Quality & Operational Excellence: Build monitoring, observability, alerts, data quality controls, and service expectations into every pipeline. Lead incident response and root-cause analysis while optimizing performance, scalability, security, and cloud cost.
Partner, Deliver & Develop Engineering Talent: Partner across Marketing, Analytics, Architecture, MarTech, and Digital Technology to deliver high-value capabilities. Mentor engineers through hands-on pairing and code reviews, raising standards and fostering accountability, curiosity, and continuous learning.
Qualifications
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; advanced degree preferred.
10+ years of hands-on data engineering or platform experience, including technical leadership of production-scale solutions and mentoring engineers.
Expert SQL and strong Python/PySpark skills across data modeling, ETL/ELT, distributed processing, orchestration, quality, observability, and performance tuning.
Hands-on experience with Azure data services such as Data Factory, Fabric, Databricks, Data Lake Storage, Synapse Analytics, Functions, or Event Hubs.
Strong GitHub and DevOps experience with code review, automated testing, CI/CD, infrastructure as code using Terraform or Bicep, and automated deployment.
Practical experience with Codex, Cursor, or GitHub Copilot, including disciplined validation of generated code, tests, security, and documentation.
Experience engineering consumer, media, customer, commerce, or marketing data from 1st party, 2nd party, and 3rd party sources in a matrixed organization.
Skills:
Apache Spark, Data Analysis, Data Engineering, Data Governance, Data Strategies, Design, Microsoft Cloud, Privacy CompliancePay Range:
United States of America: 169,000 USD - 200,000 USDBase 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:
NoJob Posting End Date:
August 27, 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.