Danone Business Services is seeking for Data and Analytics Global Lead Data Engineer based in Malaysia. With our global presence, brands and business and our mission of bringing health through food to as many people as possible; we believe that people growth is a key asset to reach a sustainable business performance.
To succeed in this journey, we're looking for the right talent and personalities eager to bring their energy and ideas to a meaningful project. Take this opportunity to GROW together and experience a culture that empowers you to express your ideas and share what you're passionate about!

1. Accountable for knowledge sharing and collaboration:
• Facilitate regular workshops, and discussions to share knowledge, tools, techniques, and best practices among data engineers.
• Encourage collaboration on common challenges and innovations, fostering a community of practice.
2. Accountable for establishing standards and best Practices:
• Define and document best practices and coding standards,
• Ensure consistency in data engineering practices across squads or teams to maintain data quality and integrity.
3. Accountable for providing technical guidance and support:
• Provide technical guidance and mentorship to data engineers, helping them solve complex problems and stay updated with the latest industry trends and technologies.
• Offer support for critical capability issues and ensure best practices in data pipeline development, data warehousing, and data integration.
4. Responsible for tooling and technology Stack:
• Evaluate and recommend tools and technologies that the organization should adopt for data engineering.
• Standardize the technology stack used for data engineering tasks to streamline operations and reduce redundancy.
5. Responsible for internals development & externals evaluation:
• Organize training sessions, certifications, and professional development opportunities to help data engineers enhance their skills and grow in their careers.
• Promote a culture of continuous learning and improvement within the chapter.
• Encourage experimentation with new techniques, and approaches to improve data engineering processes and outcomes.
• Foster an environment where data engineers can innovate and contribute to the organization's data strategy.
6. Contribute to cross-functional collaboration:
• Work closely with other chapters, such as those focused on data science, platform engineering, or data visualization, to ensure alignment and integration of data initiatives.

• Master’s degree in computer science, and/or Engineering, and/or Statistics, and/or Information Technology, and/or Information Systems, and/or Computer Engineering
• Proficiency in Azure Data Stack like Azure Databricks (Apache Spark™, Apache Spark™ SQL, Delta Lake, Delta Sharing); Azure Data Lake Storage; Azure Data Factory; Azure Event Hubs; Unity Catalog; Delta Live Tables; Databricks SQL; Azure Key Vault.
• Proved experience on End-2-End Data platforms Architectural designs and deployments, Architecture Frameworks and Methodologies.
• 5+ years’ experience in team leadership.
• 8+ years’ experience in data architecture and engineering, with indepth knowledge of working with data integration and ETL tools.
• 3+ years' experience leading data engineering team, and you are familiar with Agile working methods, as well as DevOps practices and tools.
• Strong Problem-solving oriented mindset.
• Excellent communication and teamwork abilities
• Ability to clearly explain and justify ideas when faced with competing alternatives.
• Strong aptitude for learning new technologies.