Sr. Data Engineer - Service Analytics, Reporting and AI

As a Senior Data Engineer at SAP, your key responsibilities include designing and implementing advanced data solutions that support our AI initiatives, specifically in Service Analytics, Reporting, and AI. You will work closely with cross-functional teams to integrate AI technologies with existing business applications, enhance the accuracy of data processing, and utilize Large Language Models to improve efficiency, leading to impactful enhancements in business processes.

To qualify for the Senior Data Engineer position at SAP, candidates typically need a strong background in data engineering and software development, ideally with a degree in Computer Science or a related field. Proficiency in programming languages such as Python, Java or Scala, experience with data modeling, and expertise in big data technologies like Hadoop or Spark are crucial. Familiarity with AI/ML frameworks is a plus, along with strong problem-solving skills and the ability to collaborate effectively within diverse teams.

As a Senior Data Engineer at SAP, you will have the opportunity to work with a variety of advanced technologies. This includes cloud platforms, data pipeline frameworks, and machine learning models. Specifically, you’ll be engaged with SAP’s AI tools including Generative AI Hub and Document Information Extraction, enabling you to apply innovative big data solutions and analytics that enhance enterprise-level applications.

SAP places a strong emphasis on personal development for all employees, including Senior Data Engineers. You'll have access to ongoing learning opportunities, mentorship programs, and professional growth resources tailored to enhance your skills. The company nurtures innovation by encouraging participation in workshops, conferences, and further education, helping you advance your career while making significant contributions to our technology landscape.

The workplace culture at SAP is vibrant and inclusive, focusing on collaboration and innovation among Data Engineers and all employees. SAP fosters an environment that embraces diversity, prioritizes employee well-being, and supports flexible working models. The culture encourages open communication and celebrates individual achievements, helping create a thriving community of professionals dedicated to building breakthroughs together.

In your response, focus on specific projects where you've applied data engineering principles. Highlight any relevant data tools or technologies you've used that align closely with SAP's objectives, such as data modeling and big data frameworks. Discuss how these experiences have prepared you to contribute effectively to SAP's AI initiatives.

Choose a standout project that demonstrates your technical expertise and problem-solving skills. Outline the project's objectives, your role in it, the challenges you faced, and the solutions you implemented. Emphasize any outcomes or improvements that resulted from your work, illustrating the impact you made.

Discuss the techniques and methodologies you employ to validate and clean data, such as ETL processes, data profiling, or automated testing. Highlight your attention to detail and the importance of accuracy in decision-making, especially in an enterprise environment like SAP.

Provide insight into how AI and machine learning are transforming the field of data engineering. Discuss potential applications in data processing, automation, predictive analytics, and how leveraging these technologies can enhance the value of data within organizations, particularly in relation to SAP's service offerings.

Highlight specific cloud platforms you’ve worked with, including any related tools or services that are foundational to data engineering. Discuss how cloud technologies have enabled you to build scalable data solutions and the advantages of cloud integration in data projects.

Illustrate your collaboration skills by sharing experiences where you effectively communicated with stakeholders from different departments. Emphasize the importance of understanding their needs, gathering requirements, and how you can contribute to aligning data engineering efforts with broader business goals.

Talk about your dedication to continuous learning—participating in webinars, pursuing online courses, following industry thought leaders, and engaging in forums. Emphasize how staying informed allows you to incorporate innovative practices in your work as a Senior Data Engineer.

Mention any data visualization tools you are proficient with, like Tableau or Power BI, and explain how they enhance the communication of data findings. Provide examples of how effective visualization has led to actionable insights and informed decision-making.

Discuss your skills in project management, including tools you use for tracking progress and strategies for prioritizing tasks based on deadlines, stakeholder needs, and project impacts. Highlight your ability to stay organized and focused amidst competing demands.

Share your passion for technology, innovation, and the desire to contribute to meaningful projects. Explain how SAP’s mission resonates with your personal values and how being part of a forward-thinking organization inspires you to achieve your best work.