Manager, Data Engineering
About The Position
About Us CPS (Commercial Products Supply) is a key part of the Advantaged Supply Chain of the Technical Function of The Coca-Cola Company. CPS manufactures concentrates and beverage bases for sale to bottling partners all over the world. This global organization manages a network of 19 manufacturing plants in 18 different countries along with 2 office locations (Atlanta & Drogheda, Ireland). CPS also manages complex additional materials supply chains (e.g. juice, coffee, tea, milk, etc.) on behalf of bottling partners. The Manager, Data Engineer will be responsible for the design, development, and operational excellence of the CPS data platform. This role combines people leadership, technical oversight, and strategic partnership to enable scalable, reliable, and secure data solutions that support data-driven decision-making across global plant operations and supply networks.
Requirements
- Strong proficiency in Python, SQL, and distributed data processing.
- Hands-on experience with Databricks, Snowflake, or any coding platform.
- Strong understanding of data warehousing concepts and analytical database design patterns
- Solid understanding of data architecture, ETL/ELT design, and data modeling
- Experience with cloud-native data platforms, CI/CD, and DevOps practices
- 3+ years of experience in data engineering, analytics engineering, or software engineering
- Proven experience working with cloud-based data platforms, ideally Microsoft Azure
- Bachelor’s degree in computer science, Engineering, or a related technical field required
Nice To Haves
- Experience supporting data platforms for manufacturing, supply chain, or operations environments preferred
- Familiarity of job orchestration using tools such as Azure Data Factory (ADF), AWS Glue, etc.
- Familiarity with web-based dashboards or lightweight web development is a plus
- Excellent critical thinking, analytical and problem-solving skills
- Master’s degree preferred
Responsibilities
- Serve as a senior technical leader and subject matter expert for data engineering solutions
- Design, develop, and optimize data pipelines using Azure Data Factory (ADF).
- Build and maintain high-performance, scalable data transformations using PySpark, SQL, and Python
- Define and enforce data engineering best practices, standards, and architectural patterns
- Partner with CPS stakeholders, plant teams, and analytics partners to translate business needs into technical solutions
- Lead technical design reviews and mentor other engineers, providing guidance without direct people management
- Ensure data quality, reliability, monitoring, and performance of production data pipelines
- Support roadmap planning, estimation, and prioritization for data engineering initiatives
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
