Job Description
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It With Pride.
You will provide technical contributions to the data science process. In this role, you are the internally recognized expert in data, building infrastructure and data pipelines/retrieval mechanisms to support our data needs
How You Will Contribute
You will:
- Operationalize and automate activities for efficiency and timely production of data visuals
- Assist in providing accessibility, retrievability, security and protection of data in an ethical manner
- Search for ways to get new data sources and assess their accuracy
- Build and maintain the transports/data pipelines and retrieve applicable data sets for specific use cases
- Understand data and metadata to support consistency of information retrieval, combination, analysis, pattern recognition and interpretation
- Validate information from multiple sources.
- Assess issues that might prevent the organization from making maximum use of its information assets
What You Will Bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
- Extensive experience in data engineering in a large, complex business with multiple systems such as SAP, internal and external data, etc. and experience setting up, testing and maintaining new systems
- Experience of a wide variety of languages and tools (e.g. script languages) to retrieve, merge and combine data
- Ability to simplify complex problems and communicate to a broad audience
More About This Role
The Data Engineer / Analyst will be responsible for enabling end-to-end data solutions that power business insights and decision-making within the Global MSC - Central Analytics Team, , delivering global level business impact using sophisticated tools and technologies. The ideal candidate will have strong expertise in data architecture, pipeline development, and advanced analytics within large-scale enterprise systems, especially in the FMCG Supply Chain Domain. This role requires a blend of engineering expertise and analytical skills to ensure seamless data availability, processing, and visualization across the organization.
What you need to know about this position:
In this role, you will be the backbone of our supply chain analytics ecosystem — designing data pipelines, integrating multitude of data sources from SAP, cloud-based systems, third party systems, etc. and transforming raw data into actionable insights for business stakeholders. You will spend each day working hands-on with tools such as Databricks, Alteryx, SQL, BigQuery, SAP, and Power BI to ensure the flow of clean, reliable, and timely data across the enterprise.
Beyond daily execution, you will also shape the data engineering vision for supply chain analytics by establishing best practices for data quality & governance, automating data workflows, standardizing reporting frameworks, and enabling self-service analytics. Your mission will be to build a data foundation that scales with the growing complexity of our supply chains—supporting initiatives such as inventory optimization, transport optimization, supply & demand planning, warehousing & logistics performance, and manufacturing efficiency.
- Design, build, and maintain robust ETL/ELT pipelines for the MSC CAT team across structured and unstructured data sources including but not limited to SAP (HANA, ECC, BW), ERP Systems, cloud platforms such as GCP, AWS, third party systems, etc.
- Create and maintain efficient data models optimized for analytics and reporting and Automate recurring reporting and analytics processes leveraging tools such as Databricks, Python, Alteryx, Power BI, Power Automate, PowerApps, etc.
- Develop, optimize, and manage data workflows to support effective analytics and reporting. Implement best practices in data engineering, including CI/CD, data versioning using Git, and testing frameworks and mentor team members on the same
- Collaborate with supply chain, logistics, and manufacturing stakeholders & Analytics Team Members to capture requirements and translate them into scalable data and reporting solutions.
- Serve as the key liaison between the Supply Chain Analytics team and Mondelez Digital Services & Enterprise Architecture teams to ensure secure data access, adherence to data quality & governance practices, and optimal use of the technology stack.
- Continuously explore and implement new technologies to enhance analytical capabilities within the MSC - Central Analytics Team.
What extra ingredients you will bring:
Education / Certifications:
- Bachelor’s degree in Computer Science, Data Science, Information Technology, Engineering, Statistics, or related field.
- Master’s degree in Data Analytics, Business Analytics, Supply Chain Analytics, or a related discipline preferred.
- Certifications preferred:
- Analytics: Microsoft Certified: Data Analyst Associate, Google Professional Data Engineer, Databricks Data Engineer.
- Visualization: Microsoft Power BI Data Analyst, Tableau, or equivalent.
- Data Management: DAMA Certified Data Management Professional (CDMP), AWS/GCP/Microsoft Fabric Data Certifications.
- Process Automation: Alteryx Designer Core/Advanced, Microsoft Power Platform Certifications.
- Supply Chain : Certifications such as APICS (CPIM, CSCP), Six Sigma, or equivalent are desirable.
Job specific requirements:
- Proven experience as a Data Engineer, Data Analyst, or a hybrid role in a similar FMCG/Manufacturing/Supply Chain environment.
- Strong proficiency in SQL (MS SQL, PostgreSQL) for data querying and modelling, including performance optimization.
- Hands-on experience with Databricks, Alteryx, and Python for ETL, managing end-to-end data pipelines, data processing, and analytics.
- Expertise in cloud data platforms such as GCP BigQuery, GCS, Cloud Functions, and exposure to Microsoft Fabric.
- Strong knowledge of data visualization and reporting tools (Power BI mandatory; PowerApps & Power Automate preferred).
- Experience working with SAP data sources (SAP ECC, BW, HANA).
- Familiarity with data pipeline orchestration tools and Git-based version control.
- Understanding of data governance, master data management, and best practices for security and compliance.
- Ability to work in both data engineering (infrastructure, pipelines) and data analytics (insights, reporting, storytelling) capacities.
- Strong business acumen in supply chain management (planning, inventory management, logistics, procurement, production planning) in an FMCG context.
- Excellent analytical, problem-solving, and communication skills with the ability to present technical information to business stakeholders.
- Ability to work in an agile, cross-functional team and manage multiple priorities.
Travel requirements:
Work schedule:
Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy
Business Unit Summary
At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about.
We have a rich portfolio of strong brands globally and locally including many household names such as
Oreo,
belVita and
LU biscuits;
Cadbury Dairy Milk,
Milka and
Toblerone chocolate;
Sour Patch Kids candy and
Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum.
Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen—and happen fast.
Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Job Type
Regular
Data Science
Analytics & Data Science
