Scientist, Data Analyst
Listed on 2026-03-07
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IT/Tech
Data Science Manager, Data Engineer
About The Research Team
Our approach to business is to start with facts, based in science and our passion is to work towards a better shared future to make a difference in people’s lives, communities and our planet. Our scientists help support that future and we’re looking for an individual that will support the execution of new product development initiatives designed to create the robust pipeline of innovations across categories to meet the short and the long-term priorities of the region.
The ideal candidate will have prior experience in a similar role and be eager to be part of the largest beverage company in the world.
Our approach to business is to start with facts, based in science and our passion is to work towards a better shared future to make a difference in people’s lives, communities and our planet. Our scientists help support that future and we’re looking for an individual that will support the execution of new product development initiatives designed to create the robust pipeline of innovations across categories to meet the short and the long-term priorities of the region.
The ideal candidate will have prior experience in a similar role and be eager to be part of the largest beverage company in the world.
The Role
We are seeking an organized, motivated, and analytical Data Analyst to support research and enterprise data initiatives. In this role, you will design, build, and maintain scalable data pipelines that power analytics, reporting, and operational insights across the organization. You will work closely with researchers, analysts, and business stakeholders to transform raw data into reliable, high-quality datasets that drive decision‑making. The ideal candidate has hands‑on experience with modern data tools, enjoys solving complex data problems, and is comfortable working in cloud‑based environments.
If you are passionate about building dependable data systems and want to grow your skills in data engineering and analytics, we encourage you to apply.
- Design, develop, and maintain scalable, cloud‑based data pipelines to support research and operational use cases.
- Build and manage ELT processes that transform raw data into clean, analytics‑ready datasets.
- Collaborate with scientists, analysts, and business partners to gather requirements and translate them into effective data solutions.
- Ensure data quality, reliability, governance, and security through validation, monitoring, and best practices.
- Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
- Apply best practices for version control, testing, CI/CD, and documentation of data workflows.
- Support ad hoc data analysis, reporting, and visualization efforts as needed.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related quantitative field
- 1–3 years of experience working with Python and SQL in a data analysis or data engineering role
- 1–3 years of experience building, maintaining, or supporting data pipelines and ELT processes
- Experience working with data visualization and analysis tools such as Excel, Tableau, or similar platforms.
- Strong analytical and problem‑solving skills, with the ability to work with large and complex datasets.
- Familiarity with cloud platforms such as AWS or Azure and associated data services
- Experience using version control tools (e.g., Git) and working in Agile development environments.
- Strong written and verbal communication skills, with the ability to explain technical concepts to non‑technical stakeholders.
- Experience working with operational, research, or enterprise data environments.
- Exposure to data governance, data quality frameworks, or security best practices
- Experience with modern data frameworks or orchestration tools (e.g., Airflow, dbt, or similar)
- A self‑motivated individual who can work independently while collaborating effectively with cross‑functional teams
- Someone who is detail‑oriented, curious, and eager to continuously improve data systems and processes.
- A team player who thrives in a fast‑paced, evolving environment
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