Data Test 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.

This is a newly created role within the NA Mondelez Supply Chain Intelligence organization that will require the establishment and development of testing processes, frameworks, and procedures to ensure the delivery of high-quality data assets across our supply chain intelligence platforms.

The Data Test Engineer will be responsible for validating and ensuring the accuracy, reliability, and performance of data solutions across our NA Supply Chain Intelligence (SCI) data management ecosystem.

This role involves testing across various data environments, including QA and production, and spans data architecture, technical design, and end-to-end solution enablement for data analytics. As this is a new role, one of the initial responsibilities will be to establish necessary testing processes, frameworks, and procedures. In addition, this role will need to collaborate with stakeholders to understand existing gaps and define processes that ensure the testing of data quality, transformations, integrations, and reporting systems across the Supply Chain Intelligence (SCI).

The candidate must be self-driven, and capable of taking ownership in developing these processes to help define a scalable and effective testing approach. The Data Test Engineer will play a key role in establishing the testing processes, and as such, will have a significant influence on the direction of our data integrity practices, tools, and methodologies across all SCI assets.

How you will contribute

You will:

• Design and implement robust test plans and strategies for data pipelines, ETL/ELT processes, data transformations, and integrations, with a focus on establishing foundational processes for ongoing success.

• Define clear testing criteria and collaborate closely on data flow validation, ensuring alignment with business requirements.

• Define testing in different environments, such as QA and production, ensuring comprehensive test coverage that spans from data ingestion to final reporting outputs.

• Understand the scope of testing needed for various components, including testing through to the semantic layer and reporting functionality (e.g., Power BI dashboards, KPIs, calculations).

• Recognize that this role will involve significant process-building, requiring an understanding that many tools, automated processes, and frameworks will need to be set up and formalized. You will need to balance short-term testing needs with the longer-term effort of creating repeatable and scalable processes.

• Partner with both technical (Data Architects, Developers) and business stakeholders to understand data quality needs and translate them into actionable test scenarios.

• Work with Data Solution Architects and Data Analysts to design and implement automated validation processes, and continuously optimize and improve testing methodologies and tools to improve efficiency and scalability.

• Conduct root cause analysis of data issues in production and pre-production environments and ensure timely resolution, with a focus on creating scalable testing procedures to prevent future issues.

• Maintain comprehensive test documentation (test cases, results, defect tracking) to ensure transparency and clear tracking of testing efforts.

• Participate in solution design and code review discussions to advocate for data quality and testing considerations.

• Proactively identify data quality risks and contribute to continuous improvement of testing frameworks and processes.

• Provide sign off for all projects, enhancements, and remediation across all deployments to production.

What you will bring

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

• Ability to define testing expectations and strategies for QA vs. production environments. Test through to the Semantic Layer and/or include dashboard functionality testing (e.g., Power BI, Tableau).

• Ability to understand and set up manual and automated test processes. This includes identifying the areas where processes/tools are missing and contributing to their creation.

• Strong SQL skills for querying and validating data across systems including working across excel and text files.

• Familiarity with BI tools (e.g., Power BI, Tableau) for validating reporting outputs and KPIs.

• Experience with data platforms, data ingestion tools, and programming languages (e.g., SAP ECC/BW, S4 HANA, Airflow, Au