招聘
Job Description Summary: 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 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 Py Spark
- 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.
Functional Skills
- Working knowledge of Python and SQL
- Basic experience with Py Spark 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
Related Work Experience
- 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
Education Requirements
- Bachelor’s degree in computer science, engineering, analytics, or a related technical field required
- Relevant internships, coursework, or certifications are a plus
Skills:
Data Analysis, Data Mining, Data Science, Structured Query Language (SQL), Tableau (Software)
Location(s):
Singapore
City/Cities:
Singapore
Travel Required:
00% - 25%
Relocation Provided:
No
Job Posting End Date:
May 29, 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.
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关于Coca-Cola

Coca-Cola
PublicThe Coca-Cola Company is an American multinational corporation founded in January 1892 headquartered in Atlanta, Georgia. It manufactures, sells and markets soft drinks including Coca-Cola, other non-alcoholic beverage concentrates and syrups, and alcoholic beverages.
10,001+
员工数
Atlanta
总部位置
$268B
企业估值
评价
3.7
10条评价
工作生活平衡
3.2
薪酬
3.8
企业文化
4.1
职业发展
3.0
管理层
2.5
68%
推荐给朋友
优点
Good benefits and competitive compensation
Supportive team environment and friendly coworkers
Training and development programs
缺点
Management and communication issues
High pressure and stressful work environment
Long hours and heavy workload
薪资范围
21个数据点
Mid/L4
Mid/L4 · CONA Analyst - Master Data Management
1份报告
$169,000
年薪总额
基本工资
$130,000
股票
-
奖金
-
$169,000
$169,000
面试经验
2次面试
难度
3.0
/ 5
时长
14-28周
面试流程
1
Application Review
2
Recruiter Screen
3
Hiring Manager Interview
4
Technical Interview
5
Panel Interview
6
Offer
常见问题
Behavioral/STAR
Technical Knowledge
Past Experience
System Design
Culture Fit
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