AI Cloud Data Platform Technical Product Manager

#WeAreIn for driving decarbonization and digitalization.
As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener.
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We are on a journey to create the best Infineon for everyone.
This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills.
Please let your recruiter know if they need to pay special attention to something in order to enable your participation in the interview process.
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Job Description
In your new role you will:
 

• Data Product Strategy & Design:

  • Design and develop concepts for scalable data platforms and products, encompassing data acquisition, pipelines, labeling, analytics, and AI deployment.

  • Develop detailed product requirements and technical specifications for data infrastructure and services.

  • Collaborate with data engineering, data science, and MLOps teams to design and evolve our data platform architecture on the cloud.

  • Ensure platform and product designs meet both technical and business requirements, focusing on scalability, reliability, and data governance.

• Technical Product Management:

  • Define and prioritize the product roadmap, features, and requirements for our central data platform.

  • Collaborate with engineering teams through agile methodologies to develop, deploy, and iterate on data products.

  • Ensure all data products meet the highest quality and reliability standards, implementing robust data governance and quality controls.

• MLOps & Data Pipeline Optimization:

  • Collaborate with engineering teams to build and optimize robust data pipelines and MLOps workflows to support the entire machine learning lifecycle.

  • Provide technical guidance on creating insightful dashboards and optimizing data availability lead times for various stakeholders.

  • Work with teams to integrate workflow orchestration and improve efficiency and cost at each step of the data lifecycle.

• LLM & Generative AI Integration:

  • Collaborate with engineering teams to design and develop Large Language Model (LLM) enabled platform capabilities and applications.

  • Provide technical guidance on integrating LLM agents to enhance product features, such as enabling natural language interaction with our data platforms.

• Applied Deep Learning & Analytics:

  • Collaborate with data science teams to implement and scale deep learning models that enable accurate and efficient data analysis.

  • Provide technical guidance on model deployment, monitoring, and integration with the core data platform.

• Technical Road mapping:  

  • Develop and maintain the technical roadmap for the AI data platform.

  • Identify and prioritize technical requirements, features, and innovations to ensure the platform remains state-of-the-art.

  • Collaborate with engineering and business units to align the roadmap with company-wide objectives.

Your Profile
You are best equipped for this task if you have:
 

• 6-8 years of experience  in data engineering, data science, or technical product management for data-intensive products.

• A  Bachelor's or Master's degree  in Computer Science, Electrical/Electronics Engineering, or a related field.

• Excellent  problem-solving skills  and meticulous attention to detail.

• Extensive experience with  cloud data platforms  such as  GCP  or  AWS .

• Strong technical knowledge of  data engineering, MLOps, data governance, and analytics .

• Proven experience with  technical product management  and data product design.

• Experience with  agile development methodologies  and leading cross-functional teams.

• Proficiency with data processing technologies and languages like  Python and SQL .

• Experience with  data analytics, business intelligence, and machine learning .

• Certifications  in cloud or AI technologies (e.g., Microsoft Azure Fundamentals, AWS Certified Data Engineer).

• Experience with  DevOps tools and practices .