Data Analytics
4 weeks ago
The selected candidate will join the R&D Execution Governance team at Infineon Technologies, headquartered in Munich. Under the guidance of a local mentor, the intern will work on assignments within Infineon's flagship Automotive Micro-controllers. This role offers exciting learning opportunities to be involved in and exposed to end-to-end data activities such as data automation, visualization, and data documentation and governance.
Key Responsibilities- Set up, maintain, and improve data automation pipelines for KPI reports using tools such as Python, Tableau Prep, schedulers (Jenkins), version control (Bitbucket/GitHub), tracking tools (JIRA), virtualization platforms (Denodo), and knowledge base platforms (Confluence).
- Create and maintain interactive data visualizations/reports on Tableau.
- Support the R&D Execution Governance team in organizing and documenting data assets and use cases with cataloguing tools such as Alation. This includes documenting data dictionaries and data lineages to uncover dependencies in data pipelines or data quality issues.
- Collaborate closely with key R&D stakeholders in Munich, including the Data Governance Office, Project Management Office, System/Data Owners, and data professionals in the R&D Execution Governance team, working in a SCRUM setup.
- Apply knowledge gained from coursework by working on end-to-end data use cases at R&D, touching on topics such as data engineering, analytics, and governance.
- Gain experience and knowledge in common commercial tools such as Python, Tableau, Jenkins, Bitbucket, GitHub, JIRA, Confluence, and Denodo.
- Enhance R&D efficiency and effectiveness through digitalization, data visualization, and data management.
- Experience 'learning while doing' in a dynamic and diverse team of data professionals.
- Sharpen soft skills essential for future career proliferation after graduation in a safe environment, interacting with colleagues across Asia Pacific and Europe.
- Bachelor/Master's Degree in Business Analytics/Data Science/Computer Science.
- Demonstrated skills/portfolio in scripting (SQL & Python) and data visualization (Tableau).
- Basic understanding of data governance concepts such as metadata, data classification, data access management, data architecture, and data stewardship.
- Good communication, verbal, and written skills, including the ability to effectively explain technical details to a non-technical audience.
- Demonstrated problem-solving skills to detect and resolve causes of errors in data solutions.
- High level of initiative, independence, and urgency to get things done, with an agile mindset.
- Willingness to learn and explore new tools, methods, or ways of working to improve efficiency in existing processes.
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