Director, Marketing Data Engineering

Posted 2 Days Ago
Be an Early Applicant
Atlanta, GA, USA
In-Office
169K-200K Annually
Expert/Leader
Food
The Role
Leads hands-on design, development, and operation of scalable Azure marketing data pipelines and trusted data products. Writes and reviews Python, SQL, and PySpark code; establishes GitHub, DevOps, CI/CD, infrastructure-as-code, testing, observability, and security practices. Integrates consumer, media, commerce, CRM, loyalty, Adobe, and enterprise data while applying governance, modeling, metadata, lineage, and data quality standards. Partners across marketing and technology teams, leads incident response, optimizes cloud performance and costs, and mentors engineering talent.
Summary Generated by Built In

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.

All persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form (Form I-9) upon hire.

Skills:

Apache Spark, Data Analysis, Data Engineering, Data Governance, Data Strategies, Design, Microsoft Cloud, Privacy Compliance

Pay Range:

United States of America: 169,000 USD - 200,000 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:

30

Annual 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 America

City/Cities:

Atlanta

Travel Required:

00% - 25%

Relocation Provided:

No

Job Posting End Date:

August 27, 2026

Our 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.

Skills Required

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field
  • 10+ years of hands-on data engineering or platform experience
  • Technical leadership of production-scale solutions and experience mentoring engineers
  • Expert SQL skills
  • Strong Python and PySpark skills
  • Experience with data modeling, ETL/ELT, distributed processing, orchestration, data quality, observability, and performance tuning
  • Hands-on experience with Azure data services, including Data Factory, Fabric, Databricks, Data Lake Storage, Synapse Analytics, Functions, or Event Hubs
  • Strong GitHub and DevOps experience, including code review, automated testing, CI/CD, infrastructure as code, and automated deployment
  • Infrastructure-as-code experience using Terraform or Bicep
  • Practical experience with Codex, Cursor, or GitHub Copilot
  • Experience validating AI-generated code through testing, security review, and documentation
  • Experience engineering consumer, media, customer, commerce, or marketing data from first-party, second-party, and third-party sources
  • Advanced degree

The Coca-Cola Company Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Coca-Cola Company and has not been reviewed or approved by The Coca-Cola Company.

  • Retirement Support Retirement benefits are positioned as a standout, combining a 401(k) match with a company-funded cash-balance pension and an employee stock purchase plan match that together materially increase long-term package value.
  • Healthcare Strength Health coverage is described as broad and feature-rich, including national medical coverage plus specialized add-ons like virtual care, second opinions, oncology navigation, fertility support, and chronic-condition programs.
  • Leave & Time Off Breadth Time-off benefits are outlined with structured vacation accrual that increases with tenure and a holiday program that includes both set and floating days.

The Coca-Cola Company Insights

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The Company
HQ: Atlanta, GA
88,900 Employees
Year Founded: 1892

What We Do

The Coca-Cola Company (NYSE: KO) is a total beverage company, offering over 500 brands in more than 200 countries and territories. In addition to the company’s Coca-Cola brands, our portfolio includes some of the world’s most valuable beverage brands, such as AdeS soy-based beverages, Ayataka green tea, Dasani waters, Del Valle juices and nectars, Fanta, Georgia coffee, Gold Peak teas and coffees, Honest Tea, innocent smoothies and juices, Minute Maid juices, Powerade sports drinks, Simply juices, smartwater, Sprite, vitaminwater and ZICO coconut water.

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