Data Analyst for Automotive Purchasing (f/m/div.)

As a Data Analyst for Automotive Purchasing at Bosch, your key responsibilities will include the development and implementation of dashboards aimed at digitalizing procurement processes, improving existing Power BI reports, and ensuring data integrity. You will analyze data structures, automate ETL pipelines, and support ad-hoc analyses, all while collaborating with various stakeholders within an international setting.

To apply for the Data Analyst position at Bosch, you should have a completed university degree in computer science or a related field. Extensive experience as a Power BI developer, expertise in data modeling, knowledge of ETL processes, and strong communication skills are crucial. Familiarity with agile software development practices and UX methods will be advantageous.

Bosch actively promotes career development for its Data Analysts by offering a range of training opportunities, including technical and language courses, as well as certifications. The company emphasizes continuous professional development and provides avenues for growth within the organization, ensuring that employees remain competitive and fulfilled in their roles.

Data Analysts at Bosch enjoy a collaborative and dynamic team environment. The company values diversity and encourages an exchange of ideas among team members from different backgrounds and cultures. Working internationally, you'll have the opportunity to learn from colleagues worldwide, fostering an innovative atmosphere that enhances problem-solving.

Data Analysts at Bosch can enjoy a variety of benefits, including flexible work conditions, a hybrid work system, health insurance, training opportunities, and great discounts on Bosch products. The role also offers access to fitness-related activities and conveniences like on-site medical offices and free transport from Porto.

In responding to this question, highlight specific projects where you utilized Power BI, focusing on the dashboards you created and the insights they provided. Mention any challenges you faced and how you overcame them, showcasing your problem-solving skills and your ability to use data to drive decisions.

Discuss your approach to maintaining data integrity and security, such as regular audits, validation checks, and adherence to data governance rules. Mention any tools or strategies you use to safeguard sensitive information and ensure compliance with regulations.

Elaborate on your knowledge of ETL processes, sharing specific instances where you designed or improved ETL workflows. Describe the technologies you used, the challenges faced, and the outcomes achieved to illustrate your competence in handling data from different sources.

To communicate complex data findings effectively, focus on your ability to tailor your message for different audiences. Discuss strategies such as storytelling with data, using visual aids, and presenting key insights rather than overwhelming details, ensuring your audience understands the implications of your findings.

Share a specific experience of working on a cross-functional project, emphasizing your role in facilitating communication between teams, managing deadlines, and aligning various interests. Highlight your project management skills and ability to compromise to achieve a common goal.

Discuss your preferred methods for analyzing data structures, such as utilizing SQL queries, database tools, or visualization software. Explain how you approach understanding relationships within the data and how this informs your overall analysis strategy.

Select a successful dashboard you created and describe its objectives, the tools used, and how it addressed specific business needs. Share metrics that demonstrate its impact, such as improved reporting speed or decision-making enhancements resulting from your insights.

Explain your project prioritization strategy, such as assessing project urgency, stakeholder impact, and resource availability. Provide examples of how you've effectively balanced competing tasks while maintaining quality in your deliverables.

Identify potential challenges, such as rapidly evolving technology and the need for accurate data in decision-making. Discuss how your analytical skills and adaptability would help you address these challenges effectively.

Share your strategies for staying current, such as attending workshops, participating in online forums, reading industry publications, and networking with professionals in the field. Highlight your commitment to continuous learning as essential in the fast-changing world of data analysis.