Data Eng.

Your Key Responsibilities

Data Engineering includes the collection, modeling, storage, processing, and analysis of extremely large (e.g., social media), rapidly changing (e.g., sensor data), and complex (e.g., ecological systems) data sets. ETL: Extract, Transform, Load (data). Data sets can trigger and/or affect all information processes in the business. The term "complex" refers to the massive, interconnected, and dynamic nature of the data sets to be analyzed

Key Responsibilities

•  At least 6 years of relevant professional experience in this field.
• Support in the design, implementation, and maintenance of data integration pipelines and reusable data services (ETL processes = Extract, Transform, Load processes)
• Implementation of operational database structures, optimized views, and aggregations of data from multiple data sources and IT systems (including the use of data virtualization technologies)
• Support in the design and implementation of solution-oriented data integration and provisioning architectures for data-driven business applications in AAM
• Cooperation with IT functions and business departments for data connection and data provisioning
• Documentation of various data integration pipelines, data architectures, and other reusable components
• Ensuring data quality through the development and maintenance of automated control measures
• Participation in interdisciplinary teams using agile methodologies, and taking on Data Engineering responsibilities for designing and implementing data pipelines as part of cross-functional, use-case-specific solution architectures to be coordinated with IT Solution Architects
• Management and use of Big Data technologies and environments on the Digital Platform
• Application of data-related policies for data flows, data storage, and data processing on the Schaeffler Digital Platform
• Creation of professional documents in English (oral/written)

Your Qualifications

Your Profile

• Successfully completed studies in Computer Science or similar courses of study
• At least three years of relevant professional experience
• Good understanding of Cloud Computing principles and technology
• Experience with integration of data from multiple data sources and IT systems, e.g., ERP/SAP, DWH/SAP-BW, Web Services, CRM/Salesforce, MES, etc.
• Relevant experience working in cloud environments and services; experience with Microsoft Azure is desirable, e.g., Azure Data Factory, Data Lake, IoT Hub, Databricks, etc.
• Basic programming experience in Java and/or Python; experience with software development is a plus
• Experience in Data Modeling (ER, UML) and SQL
• Very good English skills, both spoken and written; German language skills are advantageous

Team player, good analytical and communication skills