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 provide technical contributions to the data science process. In this role, you are the internally recognized expert in data, building infrastructure and data pipelines/retrieval mechanisms to support our data needs
How you will contribute
You will:
What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It with Pride
In This Role
As a DaaS 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 .
Role & Responsibilities:
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 Storage: Ensure efficient data storage and retrieval for optimal performance.
Collaborate and Innovate: Work closely with data teams, product owners, and stay updated with the latest cloud technologies and best practices.
Technical Requirements:
Programming: Python
Database: SQL, PL/SQL , Postgres SQL, Bigquery , Stored Procedure / Routines.
ETL & Integration: AecorSoft , Talend, DBT, Databricks (Optional), Fivetran .
Data Warehousing: SCD, Schema Types, Data Mart.
Visualization: PowerBI (Optional), Tableau (Optional), Looker.
GCP Cloud Services: Big Query, GCS.
Supply Chain: IMS + Shipment functional knowledge good to have.
Supporting Technologies: Erwin, Collibra, Data Governance, Airflow.
Soft Skills:
Problem-Solving: The ability to identify and solve complex data-related challenges.
Communication: Effective communication skills to collaborate with Product Owners, analysts, and stakeholders.
Analytical Thinking: The capacity to analyze data and draw meaningful insights.
Attention to Detail: Meticulousness in data preparation and pipeline development.
Adaptability: The ability to stay updated with emerging technologies and trends in the data engineering field.
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.