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.

Technology Stack: Tricentis Tosca (DI/DEX), GCP (Dataplex/Big Query), Python, Automic, CI/CD.

Role Overview

We are looking for a high-energy, technically curious Data Engineer to join our ECC to S4 GCP Automation & Testing team. Key Responsibilities include ensuring Data Reliability and Accuracy, implementing rigorous automated checks to ensure our stakeholders can trust the data for critical decision-making using TOSCA and Dataplex to achieve the same.

Key Responsibilities

• Data Validation: Design and execute automated data integrity tests using the Tosca DI (Data Integrity) module.

• Execution Management: Set up and manage Tosca DEX (Distributed Execution) agents to run large-scale test suites in parallel.

• GCP Data Governance: Use GCP Dataplex to monitor data lineages, ensuring end-to-end visibility of data movement across the platform.

• SQL Optimization: Write, debug, and optimize complex SQL queries in Big Query to validate data accuracy and performance.

• Scripting & Automation: Read and maintain Python scripts used for data processing and automated utility tasks.

• Orchestration: Assist in scheduling and monitoring data jobs using Automic (or similar enterprise schedulers).

• CI/CD Integration: Support the integration of automated tests into the CI/CD pipeline to ensure data quality at every deployment stage.

More about this role Education & Relevant experience

• Education: Master’s degree in computer science, Data Science, Information Systems, or a related technical field.
• Experience: 1-2+ years of professional experience in data engineering, automated testing, or cloud-based data quality roles.

Technical Requirements:

• Tosca Expertise: Experience working with Tricentis Tosca, specifically the DI module and DEX agent configuration.

• GCP Foundation: Familiarity with Google Cloud Platform, with a specific interest or experience in Dataplex and Data Lineage features.

• SQL Skills: Strong ability to write joins, window functions, and identify bottlenecks in SQL queries.

• Python Knowledge: Ability to read, understand, and perform troubleshooting in Python code.

• Tools: Basic understanding of Automic for job scheduling and familiarity with Git-based CI/CD workflows.

Soft Skills:

• Analytical mindset—you enjoy finding the "needle in the haystack" in large datasets.

• Adaptability to learn new cloud-native tools as the GCP ecosystem evolves.

• Clear communication skills to explain technical data gaps to stakeholders.

No Relocation support available

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, bel Vita 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: