.Helping our customers to sell more parts & make things easier with our data and solutions based on our globally leading data standards. At TecAlliance, IT and automotive specialists collaborate to digitize the automotive spare parts market. We are not just witnessing the future of the market together - we are shaping it. More than 900 colleagues work tirelessly across 140 countries, and the numbers are growing. We are owned by 34 automotive companies such as Bosch, Continental, or ZF and take pride in connecting all data for them. Become part of a great team! Our Information Management division, TecAlliance Data Factory, plays a crucial role by sourcing and standardizing automotive aftermarket data worldwide. We excel in harmonizing diverse standards from different countries' transport authorities and data providers, transforming raw data into a universally accessible 'gold standard. This standardized data forms the cornerstone of our core business. Position Overview As a Senior Data Engineer (m / f / d) in our Information Management department, you are part of a cross-functional and diverse team of IT and data-engineering professionals. You will coach and mentor data analysts and engineers, fostering knowledge exchange, to enhance digitalisation in data production and customer services in automotive aftermarket. Your Main Responsibilities: Act as a coach and mentor for a team of Data Engineers and Data Analysts, providing solution-oriented advice and technical coordination. Ensure compliance with guidelines, framework conditions, and maintain data quality, integrity, and security across all data pipelines and storage systems. Design, build, and maintain scalable data pipelines and infrastructure to support data processing, ETL workflows, and analytics. Stay updated with industry trends and best practices in data engineering to drive knowledge and continuous improvement initiatives. Consult and collaborate with internal stakeholders in the context of project management. Your Profile: Bachelor's degree in Computer Science, Engineering, or related field. 5 years of experience in data engineering, with a strong track record in designing and implementing scalable data solutions. Familiarity with industry patterns and practices in cloud-based data engineering (data warehousing, data lake, and analytics platforms). Proficiency in AWS data engineering stack, including PySpark for data processing, AWS Step Functions for workflow automation and scheduling, and other relevant AWS services. Strong understanding and hands-on experience with database technologies, including SQL and NoSQL databases. Strong analytical and conceptual skills, and a highly structured work approach. Strong sense of responsibility and accountability. Proven ability to troubleshoot issues and find practical solutions