Logistics Data Analyst Intern

Job Overview

Role: Logistics Data Analyst Intern Location: Gurgaon Experience: Freshers / Students Qualification: B.E/B.Tech/B.Sc/M.E/M.Tech/M.Sc Key Skills: Microsoft Excel, Power BI, SQL, Data Analytics, Data Modelling, Reporting, Microsoft 365, Python, Databases, SAP, Snowflake, Process Mining, AI / Machine Learning, Data Governance

Job Description

Siemens Energy Internship 2026 is hiring candidates for the position of Logistics Data Analyst Intern in Gurgaon. This internship is suitable for students currently pursuing bachelor's or master's degrees in Computer Science, Information Technology, Data Science, Business Analytics, Industrial Engineering, Supply Chain Management or related disciplines. The internship focuses on logistics data analytics, Power BI dashboards, data modelling, SQL, Excel-based analysis, data quality, reporting, process improvement and digitalisation. Interns will work alongside Logistics, IT and Data experts and gain practical exposure to global supply chain and logistics processes. The role also provides exposure to areas such as process mining, AI and Machine Learning, SAP, Snowflake, logistics automation and modern data platforms.

Roles and Responsibilities

• Power BI and Reporting: Support the creation, enhancement and maintenance of Logistics KPI dashboards. Develop and maintain management reports using Power BI. Create clear data visualizations for operational reviews and management decision-making. Support project governance and reporting activities.
• Data Preparation and Quality: Assist with data modelling and data preparation. Perform Excel-based data analysis. Support data quality corrections and validation. Collect, cleanse and validate logistics data. Monitor data quality and help maintain accurate reporting outputs.
• Logistics and Supply Chain Analytics: Analyze transport, warehouse and supply chain datasets. Identify trends, bottlenecks and opportunities for process improvement. Support Transport and Warehouse Performance Analytics initiatives. Contribute to Warehouse Analytics and Footprint Reporting activities.
• Business and IT Collaboration: Work with business and IT teams to understand reporting requirements. Validate reporting requirements and align business definitions. Help ensure data accuracy and consistency. Support workshops, testing and User Acceptance Testing (UAT). Work with stakeholders to understand analytics requirements.
• Data Governance and Documentation: Document logistics data objects, business definitions and data models. Help maintain logistics master data documentation. Support data governance documentation. Prepare data products for business users. Maintain clear process and project documentation.
• Project Management Support: Support project tracking and status updates. Track actions, milestones and follow-up activities. Maintain project documentation in project management tools. Assist project managers with logistics digitalisation initiatives. Prepare presentations, training materials and management reports.
• Global Logistics Projects and Initiatives: During the internship, candidates may gain exposure to global logistics digitalisation and analytics initiatives, including: TM4ALL OneTMS Warehouse Analytics Logistics Data Domain Logistics Process Mining AI-enabled Logistics Solutions Transport & Warehouse Performance Analytics Logistics Process Automation.

Skills and Eligibility Criteria

Educational Background: Currently pursuing a bachelor's or master's degree. Relevant disciplines include Computer Science, Information Technology, Data Science, Business Analytics, Industrial Engineering, Supply Chain Management and related fields. Eligible qualifications include B.E, B.Tech, B.Sc, M.E, M.Tech and M.Sc.

Experience: Freshers / Students.

Mandatory Technical Skills:

• Microsoft Excel: Advanced Excel knowledge is preferred.
• Power BI: Dashboard development, reporting and data visualization.
• SQL: Data extraction, querying and analysis.
• Data Analytics: Ability to identify trends, bottlenecks and improvement opportunities.
• Data Modelling: Understanding of relationships between datasets and business data structures.
• Reporting: Ability to create clear and useful management reports.
• Microsoft 365: Familiarity with Microsoft productivity and collaboration tools.

Competencies:

• Strong analytical and problem-solving abilities.
• Curiosity and willingness to learn new technologies.
• Good communication and presentation skills.
• Ability to work independently and collaborate with international teams.
• Structured and detail-oriented approach to work.
• Python knowledge is desirable.
• Databases: Understanding of database concepts is useful.
• SAP: EWM, TM, ERP or S/4HANA.
• Snowflake: Knowledge of the cloud data platform.
• Process Mining: Exposure to tools such as Celonis.
• AI / Machine Learning: Basic understanding of AI and ML concepts.
• Data Governance: Understanding of data definitions, quality and governance practices.