Description The Microsoft Fabric Data Engineer is responsible for designing, building, and maintaining scalable, secure, and high-performance data pipelines and data models within Microsoft Fabric. This role focuses on ingesting data from multiple enterprise source systems into OneLake, transforming data across Bronze, Silver, and Gold layers, and enabling trusted, analytics-ready datasets for reporting, dashboards, and advanced analytics. The ideal candidate has hands-on experience with Microsoft Fabric, Lakehouse architecture, and modern ELT patterns, and works closely with Power BI developers and business stakeholders to deliver reliable and governed data solutions. Requirements Data Engineering & Pipelines - Design, develop, and maintain end to end data pipelines in Microsoft Fabric using Pipelines, Dataflows Gen2, and Notebooks - Ingest structured and semi structured data from SQL databases, APIs, SFTP, CSV, SaaS platforms, and file based sources into OneLake - Implement incremental and full load ingestion strategies with error handling, logging, and monitoring Lakehouse & Data Modeling - Build and manage Lakehouse architectures following Bronze, Silver, and Gold data patterns - Perform data cleansing, standardization, and transformation to produce analytics ready fact and dimension tables - Optimize data models to support Direct Lake and Power BI semantic models Performance, Reliability & Optimization - Optimize pipeline execution, storage layout, and query performance across Fabric workloads - Monitor capacity usage and proactively identify performance bottlenecks - Troubleshoot and resolve data quality, pipeline, and refresh failures Security, Governance & Compliance - Implement data security controls using Microsoft Entra ID, workspace roles, and access policies - Support data governance, lineage, and cataloging through Microsoft Purview - Follow enterprise standards for data retention, privacy, and compliance (HIPAA/HITRUST where applicable) Collaboration & Delivery - Partner with Power BI Developers to ensure datasets are optimized for reporting and analytics - Work with business and analytics teams to understand data requirements and translate them into technical solutions - Support UAT, production deployments, and ongoing enhancements DevOps & Best Practices - Participate in CI/CD processes using Azure DevOps or equivalent tooling for data assets - Maintain technical documentation, data dictionaries, and pipeline design artifacts - Contribute to data engineering standards, frameworks, and reusable patterns Qualifications: Education: - Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience) Qualifications: - Hands-on experience with Microsoft Fabric (Lakehouse, Pipelines, Notebooks, OneLake) - Strong proficiency in SQL and data transformation logic - Experience with modern data architecture concepts (ELT, Lakehouse, dimensional modeling) - Experience with Azure data services (Azure Data Factory, Synapse, SQL, Storage) - Familiarity with Power BI and Direct Lake integration patterns - Experience with CI/CD for data platforms - Healthcare or regulated-industry data experience - Microsoft Fabric, Azure Data Engineer, or related certifications Skills: - Strong analytical and problem-solving skills - High attention to data accuracy, quality, and reliability - Ability to work cross-functionally with technical and non-technical stakeholders - Strong documentation and communication skills - Ability to manage multiple data initiatives in parallel

• Design, implement, and maintain data pipelines to access data sources • Develop processes for staging data, performing ETL/ELT operations and moving data to the appropriate data flows. • Collaborate with data engineers, data analysts, and business stakeholders to understand data requirements and ensure alignment to Use Case • Perform design engineering to ensure the data pipeline meets the Product’s Data Contract for currency, throughput, and performance.

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 be crucial in supporting our business by creating valuable, actionable insights about the data, and communicating your findings to the business. You will work with various stakeholders to determine how to use business data for business solutions/insights. How you will contribute You will: - Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization. In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modeling - Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business. After that you will work with stakeholders to determine how to use business data for business solutions/insights - Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor results - Apply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data - Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy - Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making - Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements What you will bring A desire to drive your future and accelerate your career and the following experience and knowledge: - Strong quantitative skillset with experience in statistics and linear algebra. - A natural inclination toward solving complex problems - Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it - Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons - Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc. - Good communication skills to promote cross-team collaboration - Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc. - Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholders More about this role What you need to know about this position: Current State Management & Optimization (Foundational Data Systems): - Manage, organize, and optimize data stored across various Microsoft applications, with a primary focus on SharePoint lists, Excel workbooks, ensuring data integrity and accessibility. - Design, develop, and maintain efficient processes for data collection, validation, transformation, and movement using tools such as Power Query, advanced Excel functions, VBA, or Power Automate/Apps, to support reporting needs. - Develop and maintain data models, logic, and aggregations required to support existing dashboards and reports (e.g., Power BI) drawing from these foundational data sources. - Collaborate closely with business users and analysts to understand their data requirements and ensure timely and accurate delivery of information. - Proactively troubleshoot data-related issues, identify root causes, and implement effective solutions to minimize disruptions and maintain data quality within the current ecosystem. - Document existing data structures, flows, and business logic to ensure clarity and maintainability. Future State Vision & Implementation (Cloud Data Modernization): - Provide technical leadership in the evaluation, selection, and eventual adoption of new cloud-based data technologies and platforms (e.g., Azure Data Lake, AWS S3/Glue/Redshift, Google Cloud Storage/BigQuery/Dataflow). - Architect and design scalable, resilient, and cost-effective cloud data lake solutions, including strategies for data ingestion, storage, processing frameworks, and data governance, in anticipation of future investments. - Develop and implement proof-of-concepts (POCs) for modern data warehousing, data lake, and big data technologies to demonstrate value and guide strategic decisions. - Serve as a technical mentor and subject matter expert on best practices for data engineering, data governance, and data security in a cloud environment. - Collaborate with IT and business stakeholders to define a forward-looking data strategy, roadmaps, and project plans for technology upgrades and migrations. - Stay abreast of industry trends, emerging technologies, and best practices in data engineering and cloud data platforms, bringing innovative solutions to the forefront. What extra ingredients you will bring: Education / Certifications: Job specific requirements: - Approximately 10 years of professional experience in roles focused on data management, data analysis, business intelligence, or similar, with a strong emphasis on data organization and transformation. - Deep and demonstrable proficiency with the Microsoft Office Suite, specifically advanced Excel capabilities (e.g., Power Query, complex formulas, VBA, Dataflow, Power BI), Access databases, and extensive experience managing data within SharePoint lists and libraries. - Proven experience in supporting and enhancing business intelligence dashboards and reporting tools (e.g., Power BI) from diverse data sources. - Experience with Microsoft Power Automate, Power Apps, or other low-code automation tools for data orchestration. - Experience with scripting languages such as Python or VBA for data manipulation or process automation. - Exceptional ability to manage, cleanse, structure data effectively, even in non-traditional database environments. - Excellent problem-solving skills, with the ability to diagnose complex data challenges and provide practical solutions. - Strong analytical mindset with a clear aptitude and eagerness to learn, evaluate, and strategically implement new, complex cloud-based data technologies. - Strong communication skills, both written and verbal, with the ability to articulate technical concepts clearly to both technical and non-technical stakeholders. - A plus but not required, Familiarity with data governance, data quality, and metadata management practices. Travel requirements: Adhoc Work schedule: Mid Shift 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 Data Science Analytics & Data Science

• Manage and guide data teams with hands-on experience to execute on enterprise data strategy. • Provide technical guidance for the team, raise the bar on the latest data technologies, and mentor data resources. • Design, develop, and implement end-to-end EDW data processing encompassing multiple Data Marts. • Build and manage scalable data pipelines to load EDW and data science environments. • Automate data operations to manage 100s of pipelines. • Automate data validation and testing of pipelines. • Collaborate with engineering teams to productionize data pipelines with high reliability and performance.