Senior Data Engineer

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.

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

How you will contribute

You will:

• Work in close partnership with the business leadership team to execute the analytics agenda
• Identify and incubate best-in-class external partners to drive delivery on strategic projects
• Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance
• Execute the business analytics program agenda using a methodical approach that conveys to stakeholders what business analytics will deliver

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Using data analysis to make recommendations to senior leaders
• Technical experience in roles in best-in-class analytics practices
• Experience deploying new analytical approaches in a complex and highly matrixed organization
• Savvy in usage of the analytics techniques to create business impacts

In This Role

As a Senior 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, PySpark, Go/Java
• Database: SQL, PL/SQL
• ETL & Integration: DBT, Databricks + DLT, AecorSoft, Talend, Informatica/Pentaho/Ab-Initio, Fivetran.
• Data Warehousing: SCD, Schema Types, Data Mart.
• Visualization: Databricks Notebook, PowerBI (Optional), Tableau (Optional), Looker.
• GCP Cloud Services: Big Query, GCS, Cloud Function, PubSub, Dataflow, DataProc, Dataplex.
• AWS Cloud Services: S3, Redshift, Lambda, Glue, CloudWatch, EMR, SNS, Kinesis.
• Azure Cloud Services: Azure Datalake Gen2, Azure Databricks, Azure Synapse Analytics, Azure Data Factory, Azure Stream Analytics.
• Supporting Technologies: Graph Database/Neo4j, Erwin, Collibra, Ataccama DQ, Kafka, 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.

Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy

Business Unit Summary

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