Data Product Owner
Zeiss
Product Owner (f/m/d) for Data Lifecycle applications
You will play a crucial role in steering the development of data lifecycle tools to support users to manage their data, metadata and knowledge in operations. In this way, you actively contribute to the success of the digital transformation at ZEISS, driven by ZEISS Digital Partners.
Given the ZEISS-wide and inter-disciplinary relevance of data lifecycle Management, you will closely collaborate with stakeholders from ZEISS business units and from ZEISS Digital Partners.
Your direct roles and responsibilities are:
Requirements:
Excellent university degree in Computer Science, Business Informatics, Mathematics, Natural Science or in a related field3-7 years of relevant professional experience:Strong experience as a Product Owner in a data/ data product related fieldStrong communication, presentation, and project management skills Experience in stakeholder management; The ability to understand customer needs and effectively demonstrate strong problem-solving skills to address practical challengesExperience with cloud-deployed software solutions; The ability to understand the technical architecture of data management solutionsExperience with cloud technologies like Microsoft AzureKnowledge of best practices in corporate data governance (e.g., working with confidential data, data contracts, metadata handling)Agile software development using Scrum / KanbanBest-practices and implementation for continuous integration / deliveryProductionalising and publishing scalable data servicesTechnical know-how (basic knowledge and the motivation to learn required):Experience in implementing data contract and data quality assessment solutions in a data mesh setupExperience in modern data management frameworks: Spark-based data transformations (Databricks, Azure Synapse), search engines (Elastic), graph databases and analytical or in-memory database systems (SQL and No-SQL)Development skills in RESTful microservice with Python/Java/ScalaKnowledge in data modelling, pipeline orchestration and scheduling (ex: Airflow) and data Artifacts deployment (ex: Azure DEVOPS, Gitlab)Knowledge about cloud or on-prem data storages (Azure Blob, AWS S3) and their interrogation (SQL)Knowledge about container-based technology (ex. Azure Web-app, Azure Kubernetes Service)Experience with monitoring and logging is a plus (Elastic, Datadog, Witboost)A strong customer-oriented mindset, UI/UX experience is a plusAn independent, conscientious and solution-oriented way of workingFluency in EnglishYour ZEISS Recruiting Team:
Bartha Györgyi, Fedor Fanni, Meláth Laura, Sturcz Noémi, Sztaskó Daniella, Wenner Lili
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