Data & AI Engineering Internship

Are you passionate about data and analytics and eager to drive significant business impact? Procter & Gamble is looking for interns interested in various roles within the data and analytics domain, including Data Engineers, Data Asset Managers, and AI Engineers. You will have the opportunity to apply innovative technologies to solve complex business problems and contribute to data-driven decision-making. 

The work you will be doing could range from analyzing large datasets to providing actionable insights, managing data assets to ensure data quality and accessibility, to engineering robust data pipelines that feed analytical models and support business operations. Regardless of the specific role, as a Data, Analytics, & AI Engineering intern, you will be someone who leverages data to solve business problems. 

Example Responsibilities by Role Type: 

• Data Engineer: Design, build, and maintain cloud-based data and analytics platforms and data pipelines that acquire, cleanse, transform, and publish data from a wide range of sources. Develop large, complex datasets that support both functional and non-functional business requirements, while partnering with data asset managers, architects, and development leads to deliver high-quality, fit-for-purpose data solutions aligned with enterprise architecture standards. Contribute to and apply coding standards and best practices to create efficient, scalable, and reusable services and components. Design and implement process improvements that enhance operational efficiency, data quality, and overall platform performance.

• AI Engineer: Drive proof-of-concept development and experimental initiatives to evaluate emerging technologies, advanced models, and innovative solutions. Engineer high-quality, standards-compliant, and rigorously tested software while contributing reusable code, frameworks, and tools to shared repositories, enterprise libraries, and open-source projects in alignment with P&G IT policies. Design, develop, and optimize data models, feature engineering capabilities, data quality assurance processes, ETL/ELT pipelines, and scalable distributed computing architectures. Deploy, monitor, and enhance algorithmic solutions across cloud platforms, leveraging cloud-native services to ensure reliability, scalability, efficiency, and business impact.

• Data Asset Manager: Leading data governance activities aligned with the organization’s data strategy within assigned areas of accountability. Serve as trusted advisors to business partners, influencing strategic decisions and driving the continuous improvement of data governance practices. Oversees critical data management functions such as data quality, data operations, storage, reference and master data, data standards, security, vendor governance, and metadata management to ensure data is accurate, secure, accessible, and fit for business use.

As an intern, you will experience a subset of the above responsibilities