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.A Snapshot of your Day: As a Data Engineer, your typical day will include meetings with colleagues in the business who are seeking solutions to data challenges and to understand their requirements. Your overall focus will be to improve the availability and quality of existing data and to create a high-quality architecture as a basis for the sustainable implementation of AI use cases. You will collaborate with data engineers, data scientists, central functions, and external partners to implement AI use cases. Your role also includes business trips to understand and support local processes. How You'll Make an Impact As a data engineer, you work in an interdisciplinary team with data scientists and business professionals to foster a data-driven company culture and help to implement machine learning and AI use cases. Support business professionals in use case refinements to identify promising use cases with high business impact. Collection, maintenance, preparation, enrichment, validation, and distribution of data. Support staff in data acquisition techniques and ensure proper data collection/storage for administrative processes and on site. Plan and create a suitable system infrastructure for applications for analysis. Design and configuration of robust data sets and databases. Maintain and develop existing data infrastructure. Support conception and provision of a system architecture. Build up deep knowledge with Snowflake model. What You Bring Must have University degree in computer or data science or related field. Knowledge of Snowflake SQL Scripting, Alteryx, SnapLogic. Knowledge in building end-to-end data pipelines. Experience in data migration. Intercultural communication and collaboration skills. Agile mindset and organizational/planning skills with the ability to work on multiple complex projects. Willingness to travel with a focus on central Europe (~30%). Very good English skills. Good to have added advantage: Ideally having a track record and/or experience in data acquisition techniques. Experience in DevOps and familiarity with GitLab for CI/CD. Experience with MS Power Automate. Experience in building data ingestion pipelines using AWS, Azure data services. Experience and interest in data science and data analytics. Experience and interest in machine learning and AI. German language skills. About: Basic research is a key driver for innovation within Grid Technologies. We drive our innovation campaigns, collaborate with internal and external partners, and directly support product development with deep and profound technological expertise. During this process, we create and collect a huge amount of data that we need to take a closer look at. In the upcoming years, we will further deep dive into the potentials of process digitalization, machine learning, and generative AI. Therefore, we need high-quality, validated data available in the right format and structure to further evaluate them