$ cat jobs/it-engineer-data-lakehouse-continental-9e46944e9795.json
IT engineer data lakehouse
Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent, and affordable solutions for vehicles, machines, traffic and transportation. In 2023, Continental generated sales of €41.4 billion and currently employs around 200,000 people in 56 countries and markets. Guided by the vision of being the customer's first choice for material-driven solutions, the ContiTech group sector focuses on development competence and material expertise for products and systems made of rubber, plastics, metal, and fabrics. These can also be equipped with electronic components in order to optimize them functionally for individual services. ContiTech's industrial growth areas are primarily in the areas of energy, agriculture, construction, and surfaces. In addition, ContiTech serves the automotive and transportation industries as well as rail transport. The IT Digital and Data Services Competence Center of ContiTech caters to all the Business Areas in ContiTech and responsible among other on areas of Data & Analytics, Web and Mobile Software Development and AI The team for Data services specializes in all platforms, business applications and products in the domain of data and analytics, covering the entire spectrum including AI, machine learning, data science, data analysis, reporting and dashboarding. - Design, develop, and operate scalable and maintainable data pipelines in the Azure Databricks environment - Develop all technical artefacts as code, implemented in professional IDEs, with full version control and CI/CD automation - Enable data-driven decision-making in Supply Chain Management (SCM) by ensuring high data availability, quality, and reliability - Implement data products and analytical assets using software engineering principles in close alignment with business domains and functional IT - Apply rigorous software engineering practices su
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