Global Supply Chain Analytics Tech Lead

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.
Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results.
How you will contribute
You will:

• Work in close partnership with the business leadership team to execute the analytics agenda
• Identify and incubate best-in-class external partners to drive delivery on strategic projects
• Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance
• Execute the business analytics program agenda using a methodical approach that conveys to stakeholders what business analytics will deliver

What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:

• Using data analysis to make recommendations to senior leaders
• Technical experience in roles in best-in-class analytics practices
• Experience deploying new analytical approaches in a complex and highly matrixed organization
• Savvy in usage of the analytics techniques to create business impacts

As part of the Global MSC (Mondelez Supply Chain) Data & Analytics team, you will support our business to uncover trends that can drive long-term business results.
In this role, you will be a key technical leader in developing our cutting-edge Supply Chain Data Product ecosystem. You'll have the opportunity to design, build, and automate data ingestion, harmonization, and transformation processes, driving advanced analytics, reporting, and insights to optimize Supply Chain performance across the organization. You will play an instrumental part in engineering robust and scalable data solutions, acting as a hands-on expert for Supply Chain data, and contributing to how these data products are visualized and interacted with.
What You Will Bring
A desire to drive your future and accelerate your career and the following experience and knowledge:

• SAP Data Expertise: Deep hands-on experience in extracting, transforming, and modeling data from SAP ECC/S4HANA (modules like MM, SD, PP, QM, FI/CO) and SAP BW/HANA. Proven ability to understand SAP data structures and business processes within Supply Chain.
• Cloud Data Engineering (GCP Focused): Strong proficiency and hands-on experience in data warehousing solutions and data engineering services within the Google Cloud Platform (GCP) ecosystem (e.g., BigQuery, Dataflow, Dataproc, Cloud Composer, Pub/Sub).
• Data Pipeline Development: Design, build, and maintain robust and efficient ETL/ELT processes for data integration, ensuring data accuracy, integrity, and timeliness.
• BI & Analytics Enablement: Collaborate with data scientists, analysts, and business users to provide high-quality, reliable data for their analyses and models. Support the development of data consumption layers, including dashboards (e.g., Tableau, Power BI).
• Hands-on experience with Databricks (desirable): ideally deployed on GCP or with GCP integration for large-scale data processing, Spark-based transformations, and advanced analytics.
• System Monitoring & Optimization (desirable): Monitor data processing systems and pipelines to ensure efficiency, reliability, performance, and uptime; proactively identify and resolve bottlenecks.
• Industry Knowledge: Solid understanding of the consumer goods industry, particularly Supply Chain processes and relevant key performance indicators (KPIs).

What extra ingredients you will bring:

• Excellent communication and collaboration skills to facilitate effective teamwork and Supply Chain stakeholders' engagement. Ability to explain complex data concepts to both technical and non-technical individuals.
• Experience delegating work and assignments to team members and guiding them through technical issues and challenges.
• Ability to thrive in an entrepreneurial, fast-paced setting, managing complex data challenges with a solutions-oriented approach.
• Strong problem-solving skills and business acumen, particularly within the Supply Chain domain.
• Experience working in Agile development environments with a Product mindset is a plus.

Education / Certifications:

• Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, Engineering, or a related field.
• 6+ years of hands-on experience in data engineering, data warehousing, or a similar technical role, preferably in CPG or manufacturing with a strong focus on Supply Chain data.

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
Analytics & Modelling
Analytics & Data Science