• Own backend and data architecture across marketing data pipelines, connector systems, platform APIs, agent/tool runtimes, and downstream product surfaces, defining durable domain boundaries and data contracts between warehouse outputs, platform APIs, agent tools, and user-facing workflows. • Turn ambiguous platform needs into incremental technical plans that balance reliability, security, tenant isolation, developer experience, and long-term maintainability. • Lead the evolution of data pipelines following the medallion architecture, driving data quality, schema enforcement, lineage, and curated outputs for analytics and product use cases. • Harden ingestion from external marketing platforms and related APIs, including connector and reconciliation patterns. • Architect backend services across API paths and cloud infrastructure, shaping how platform capabilities are exposed through stable contracts, streaming workflows, and tool permissions. • Implement secure authentication, authorization, rate limiting, and multi-tenant access controls across services. • Write high-quality, production-ready code and integrate with external APIs, cloud services, and internal microservices. • Build and maintain deployment pipelines and infrastructure environments, implementing tracing, structured logging, metrics, and alerting to ensure reliability, latency, and operational standards. • Mentor engineers, contribute to internal libraries, backend frameworks, and drive consistency across the platform.

Job Description Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It Uniquely Yours. Media Data Platform team owns the collection, distribution of media data and operates services that provide near real-time operational views of consumer touchpoints. We maximise capture, storage, analysis of our billions of impressions and tags, and apply analytics, algorithms and visualisation to drive media performance monitoring, new insight creation and activation automation back in the ad tech stack. Following our organization's exciting shift toward a product-oriented approach, we are evolving our data capabilities to deliver direct, high-impact value to our business stakeholders. We are seeking a versatile Full Stack Engineer with a strong foundation in Data Engineering to join our Media Data Platform team. In this role, you will be the bridge between complex data infrastructure and user-facing solutions. Position overview The Full Stack Engineer adheres to business and technical standards, policies, and procedures throughout the software delivery lifecycle whilst accurately sizing and estimating the effort required to deliver technical solutions. You will develop, build, configure, customise, integrate, and test high-quality solutions based on functional and technical requirements. You will follow Agile methodologies and principles through work outputs and behaviours. You will work with other Product Team members (e.g., Product Owner, Business Analyst) to ideate software solutions. You will act as the champion and advocate via a thorough understanding of Google cloud technologies, helping to deploy Big Data solutions, provide guidance for vendors designated to build and manage data pipelines & ETL processes, and cloud data migrations in a production, secure and scalable manner. How You Will Contribute In this role, you will collaborate with external vendors and internal stakeholders to bridge the gap between complex data engineering and real business impact. You will work with project resources to provide design collateral and to configure software components that are aligned with security policy and governance, ensure adherence configuration standards and processes, and share your knowledge of the technology with relevant stakeholders. Key Responsibilities - Data Engineering & Pipeline Management: Own and advance our internal media data platform. Partner with external vendors to design, build, and optimize robust data pipelines connecting various media platforms. - Full-Stack Product Development: Transition data into actionable products. Design, develop, and maintain internal reporting tools, interactive dashboards, and AI-driven solutions. - Product-Oriented Execution: Adopt a product mindset-ensuring scalability, reliability, and a great user experience for all internal data tools. - Data Governance & Quality: Ensure data integrity, consistency, and security across all pipelines and downstream applications. - Manage suppliers who build and maintain the digital data platforms and drive continuous improvement and optimization programs. Ensure the consistent application of software engineering best practices (e.g. version control, testing, continuous integration) - Ensure that all data integration infrastructure works as designed (API, orchestration, SFTP etc.) - Provide cleaned, transformed data sets ready for analysis through various delivery mechanisms: flat file extracts, data marts, API - Maintain data documentation & definitions - Facilitate change management and continuous improvement to maximize user adoption and business value. Qualifications & Experience Required: - Bachelor's degree in Business, Engineering, Information Systems, or related field (or equivalent experience). - 5+ years in IT solution ownership, application management, or product ownership - preferably with Google Cloud solutions - Hands-on experience with Google Cloud, BigQuery, DBT - Knowledge of tools, methodology for achieving the best-in-class data management (SQL, Python, PySpark, Airflow) - Experience working with visualisation tools like PowerBI, Tableau, Google Looker Studio - Experience in media data engineering and adtech data integration challenges. What You Will Bring A desire to drive your future and accelerate your career. You will bring experience and knowledge in: - Industry experience with data transformation technologies such as DBT. - A strong command of SQL. - Practical experience with statistical techniques and methods such as regression analysis and distributions. - Awareness of industry best practice in data warehousing and management for large volumes of structured/unstructured data. Skills & Competencies - Exceptional communication and influence skills - able to engage senior leaders, translate complex regulatory/tech topics, and drive consensus. - Analytical mindset with focus on data accuracy, cost optimization, and sustainability impact measurement. - Proactive, results-oriented; thrives in fast-paced, evolving data environments. - Strong project management and prioritization abilities across multiple global initiatives. Work schedule: The responsibilities of this position are performed within the framework of a regional business model that is defined and managed by Mondelēz Europe GmbH, Switzerland. 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, 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 Software & Applications Technology & Digital

• Own and evolve streaming data pipelines that power live inference and real-time model serving across Kraken's AI infrastructure • Design and build feature stores that serve low-latency, high-reliability features to production ML models • Implement and maintain streaming systems using RisingWave, Apache Flink, or Kafka Streams, selecting the right tool for the workload • Partner with ML engineers and AI infra teams to define data contracts, feature schemas, and pipeline SLAs • Drive pipelines toward real-time where batch exists today reducing latency from hours to seconds • Ensure data quality, observability, and auditability across all streaming and feature engineering systems • Contribute to inference pipeline tooling where data engineering and model serving intersect • Evaluate emerging streaming and feature store technologies and shape the team's technical roadmap

• Own and evolve streaming data pipelines that power live inference and real-time model serving across Kraken's AI infrastructure • Design and build feature stores that serve low-latency, high-reliability features to production ML models • Implement and maintain streaming systems using RisingWave, Apache Flink, or Kafka Streams, selecting the right tool for the workload • Partner with ML engineers and AI infra teams to define data contracts, feature schemas, and pipeline SLAs • Drive pipelines toward real-time where batch exists today reducing latency from hours to seconds • Ensure data quality, observability, and auditability across all streaming and feature engineering systems • Contribute to inference pipeline tooling where data engineering and model serving intersect • Evaluate emerging streaming and feature store technologies and shape the team's technical roadmap