Data Engineer

Are you ready to make it happen?

You provide software and application knowledge to support implementation of the given solutions.

How you will contribute:

• You will ensure that delivered services are optimized to meet business demands and the service operations strategy, plan, measure, report and communicate service improvement initiatives, and serve as a consultant on issues and resolutions.
• You will also recommend actions that can be taken to optimize investments and benefits and to mitigate risks.
• This role will require you to identify suppliers, evaluate them, onboard new vendors, establish and run vendor governance; collaborate with management and follow up on requisitions, purchase orders, invoices, and payments; work with project resources to provide design collateral and to configure software components so they are aligned with security policy and governance; and ensure adherence to development and configuration standards and processes.

What you will bring:

A desire to drive your future and accelerate your career. You will bring experience and knowledge in:

• Working collaboratively with multiple vendors
• Leading complex projects - project management
• Stakeholder management and influencing skills
• Managing infrastructure services delivery, support and excellence
• Working in a global IT function with regional or global responsibilities in an environment like Mondelez International
• Working with IT outsourcing providers using frameworks such as the IT Infrastructure Library
• Working with internal and external teams and leading when necessary

More about this role:

As a Data COE Sr. 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 and 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, data product managers, and stay updated with the latest cloud technologies and best practices.
• Grooming juniors: Guide and groom associate data engineers and data engineers (external/internal) to ensure timely deliverables fulfilling all data engineering guidelines and standards.

What extra ingredients you will bring:

• Problem-Solving: The ability to identify and solve complex data-related challenges.
• Communication: 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.
• 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.

Technical Requirements:

• Programming: Python, PySpark, SQL
• ETL and Integration: Databricks (Mandatory), AecorSoft/DataSphere
• Data Warehousing: SCD Types, Fact and Dimensions, Star Schema, ETL
• Data Modeling: Erwin (Optional)
• Medallion Architecture: Bronze, Silver, Gold, Platinum
• AWS Cloud Services: S3, Glue, Redshift, Lambda, EMR, Athena
• GenAI exposure: Gemini/Genie/Kiro etc.
• Supporting Technologies: Databricks Jobs, Airflow
• Visualization (Optional): Power BI (Optional), Tableau (Optional), GenBI (Optional)