Data Engineer

Job description

Introduction: As a Senior Data Engineer, you will be at the heart of our data operations, taking on the most challenging and impactful projects. You will be instrumental in shaping our data architecture, designing innovative data products, and ensuring the stability and efficiency of our core data platform. This role requires a blend of deep technical expertise, strategic thinking, and a passion for mentoring. Key Responsibilities Architectural Conception: In close collaboration with the Enterprise Data Architect, you will devise and conceptualize solutions for complex data integration tasks in a multi-platform environment, including Databricks, SAP BDC, and Microsoft Fabric. Data Product Design: You will lead the design of corporate data products, transforming multiple and heterogeneous data assets from SAP, Microsoft, and other diverse systems into valuable, reliable, and scalable resources for the business. Platform Ownership: You will hold the functional responsibility for the Data Layer of our central Databricks platform, ensuring its optimal performance, governance, and evolution. Project Supervision: You will oversee international data integration projects, providing technical guidance and ensuring alignment with global standardization goals and best practices. First Hand Development: You will also implement proof o concepts, templates on which more junior colleagues will follow up on the Databricks platform. The usage of agentic coding will be part of the daily work. Required Qualifications: SQL Mastery: A minimum of 5-10 years of excellent, first-hand experience writing and optimizing complex SQL queries. Database Expertise: Over 5-10 years of demonstrable, in-depth experience with database systems. Big Data Proficiency: Deep, hands-on knowledge of the Databricks ecosystem, particularly Delta Lake and Apache Spark. Development Background: Proven, first-hand experience in software development with languages such as C (and its derivatives like C++ or C#), Java, or Python. Experience with integrated CI/CD pipelines orchestrated by GitHub actions Efficiency Focus: A profound awareness and practical approach to performance tuning, execution optimization, and cost management in large-scale data environments. Certifications (Highly Preferred) Databricks Certified Data EngineerProfessional Databricks Certified Cloud Service Provider Specialist (e.g., AWS Certified Data Engineer, Azure Data Engineer Associate) Soft Skills Global Communication: Excellent communication and interpersonal skills, with the ability to work effectively in a diverse, multi-cultural context. Mentorship: A genuine motivation to teach, explain complex topics, and actively contribute to the growth and development of junior colleagues.