Together with analytics team leaders youwill support our businesswith excellent data models to uncover trends that can drive long-term business results.

Use models/algorithms to uncover signals/patterns and trends to drive long-term business performance
A desire to drive your future and accelerate your career and the following experience and knowledge:
Using data analysis to make recommendations to analytic leaders
Knowledge of BI tools like Tableau, Excel, Alteryx, R, Python, etc. As a Data COE Data Engineer, you will have the opportunity to design and build scalable, secure, and cost-effective cloud-based data solutions. You will develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes, ensuring data quality and validation processes to maintain data accuracy and integrity. You will ensure efficient data storage and retrieval for optimal performance, and collaborate closely with data teams, product owners, and other stakeholders to stay updated with the latest cloud technologies and best practices.
Experience: Data Engineering: 3 to 7 years with good expertise in required tech stack.
Programming: Python, PySpark, SQL
ETL & Integration: Data Warehousing: SCD Types, Fact & Dimensions, Star Schema, ETL
Data Modeling: Dimensional modelling understanding, Erwin tool (Optional)
Bronze, Silver, Gold (Databricks Medallion Architecture)
AWS Cloud Services: S3, Lambda, EC2, Glue, Redshift
Design and Build: Develop and implement scalable, secure, and cost-effective cloud-based data solutions.
Manage Data Pipelines: Develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes.
Ensure Data Quality:



Implement data quality and validation processes to ensure data accuracy and integrity.
Optimize Data Processing & Storage: Ensure productive data processing of pipelines & data storage for optimal retrieval performance.
Collaboration: Be an integral part of the delivery team by exhibiting close coordination within the assigned team to ensure timely completion of deliverables fulfilling all data engineering guidelines & standards.
Problem-Solving: The ability to identify and solve complex data-related challenges.
Effective communication skills to collaborate with Engineering Leads, Data Product Managers, Data Modeler, Data Analysts, and stakeholders.
Analytical Thinking: The capacity to analyze data and draw meaningful insights.
Meticulousness in data preparation and pipeline development.
Adaptability: The ability to stay updated with emerging technologies and trends in the data engineering field.

No Relocation support available
Business Unit Summary

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 , and biscuits , and chocolate candy and gum. 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.

Analytics & Data Science

📌 Data Engineer (AWS, SQL) (Mumbai)
🏢 Cadbury
📍 Mumbai