Data Engineering Lead - Finance

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.

In This Role

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.  

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 architects, data modelers, product owners, and stay updated with the latest cloud technologies and best practices.
• Team Lead: Create & lead a team of data engineers (external/internal) to ensure timely deliverables fulfilling all data engineering guidelines & standards.

Technical Requirements:

• Programming: Python
• Database: SQL, PL/SQL, Postgres SQL, Bigquery, Stored Procedure / Routines.
• ETL & Integration: AecorSoft/DataSphere, DBT, Databricks (Optional)
• Data Warehousing: SCD Types, Fact & Dimensions, Star Schema
• Data Modeling: Erwin (Optional)
• Medallion Architecture: Bronze, Silver, Gold, Platinum
• GCP Cloud Services: Big Query, GCS, Cloud Function/Run, GKE
• Supporting Technologies: Airflow (Composer), Automic.
• Visualization (Optional): PowerBI (Optional), Tableau (Optional)

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.

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.  

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 architects, data modelers, product owners, and stay updated with the latest cloud technologies and best practices.
• Team Lead: Create & lead a team of data engineers (external/internal) to ensure timely deliverables fulfilling all data engineering guidelines & standards.

Technical Requirements:

• Programming: Python, PySpark, SQL
• ETL & Integration: Databricks (Mandatory), AecorSoft/DataSphere,
• Data Warehousing: SCD Types, Fact & Dimensions, Star Schema
• Data Modeling: Erwin (Optional)
• Medallion Architecture: Bronze, Silver, Gold, Platinum
• AWS Cloud Services: Glue, Redshift, Lambda, EMR, Athena
• GenAI exposure: Gemini/Genie/Kiro etc.
• Supporting Technologies: Airflow (Composer), Automic.
• Visualization (Optional): PowerBI (Optional), Tableau (Optional)

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.





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

Analytics & Modelling

Analytics & Data Science