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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 Data Analyst will support the design, development, and operation of data pipelines and platforms used across CPS plant operations and supply networks. This is a hands-on, entry-to-mid level technical role focused on building, testing, and supporting data engineering solutions under the guidance of senior data engineers.
Function Related Activities / Key Responsibilities
- Assist in building and maintaining batch data pipelines using Python, SQL, and PySpark
- Support data ingestion from APIs, databases, and operational systems
- Develop and test data transformations and analytics-ready datasets
- Help configure and maintain orchestrated workflows using Azure Data Factory (ADF)
- Perform data validation and reconciliation to ensure accuracy and completeness
- Monitor data pipelines and assist with troubleshooting production issues
- Participate in code reviews and follow established engineering standards
- Collaborate with senior data engineers to translate business requirements into technical solutions
- Maintain documentation for pipelines, datasets, and data processing logic
- Create reports and analytics for key stakeholders.
- Working knowledge of Python and SQL
- Basic experience with PySpark or distributed data processing concepts
- Familiarity with Azure Data Factory (ADF) or similar orchestration tools
- Understanding of ETL/ELT concepts and data pipeline fundamentals
- Experience querying data in cloud data warehouses (Snowflake, Synapse, etc.)
- Familiarity with Git and collaborative development workflows
- Willingness to learn production data engineering best practices
- Excellent critical thinking, analytical and problem-solving skills
- 1–3 years of experience in data analytics, data engineering, or software engineering
- Exposure to data pipelines, ETL/ELT processes, or analytics engineering
- Experience working with cloud-based data platforms is a plus
- Experience in manufacturing, supply chain, or operations environments preferred
- Bachelor’s degree in computer science, engineering, analytics, or a related technical field required
- Relevant internships, coursework, or certifications are a plus
Data Mining; Structured Query Language (SQL); Tableau (Software); Data Science; Data Analysis
Key Skills
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