Data Analyst Intern, CSI, AP_SG

Customer Solutions & Innovation (CSI) is DHL's cross-divisional commercial and innovation unit. In today's highly competitive market, CSI enhances the DHL customer experience by providing a single customer interface and developing innovative, industry-tailored solutions for our largest global and most strategically important customers.

We work closely with colleagues across the Business Units to deliver value beyond customer expectations and to build stronger relationships with key decision-makers. Our focus is on understanding our customers businesses and industry challenges, and on applying proven DHL solutions to address them.

We are currently seeking a Finance Intern - Data Analyst. This position reports to the Senior Manager, Data & Discovery Management, and will be closely involved in Finance Digitalization projects.

Responsibilities:

.Assist in optimizing and enhancing Databricks notebooks and Azure Data Factory (ADF) pipelines to improve data load performance and efficiency.

.Support the use of Azure cloud resources (e.g., Data Factory, Data Lake, Synapse, Databricks) in alignment with the company's data framework and architecture.

.Contribute to the delivery of high-quality, tested solutions, and support deployment into production environments.

.Work with the team to understand project requirements, methodologies, and end-to-end execution of data engineering initiatives.

.Create and maintain documentation for processes, workflows, and project deliverables to ensure knowledge sharing and process improvement.

.Explore and experiment with emerging technologies such as Generative AI (GenAI) to assess opportunities for optimizing business processes.

.Participate in data mining, collection, processing, and cleansing activities to ensure accuracy, consistency, and readiness for reporting and analysis.

.Assist the team with customer research-related work, including gathering, analyzing, and preparing insights to support business decision-making.

Requirements:

• Academic background in Finance, Statistics, Mathematics, Computer Science, Engineering, Data Science, or Analytics is a plus.
• Basic knowledge of data extraction, transformation, and data mining, with exposure to programming tools (Python & SQL).
• Familiarity with cloud platforms (preferably Azure) and interest in working with services such as Databricks, Data Factory, and Data Lake.
• Some hands-on experience or coursework in Machine Learning, Statistics, Natural Language Processing (NLP), or Text Mining is advantageous.
• Interest in emerging technologies, such as Generative AI (GenAI), and their application to business and data engineering use cases.
• Strong communication and collaboration skills able to work effectively with cross-functional and cross-geographical teams.
• Analytical mindset with attention to detail able to assist with customer research and preparation of insights to support decision-making.
• Passion for technology, self-motivated, and a positive, can-do attitude.
• Open to students who are able to commit during: Jan - Jun 2026.