It Engineer Data Lakehouse

Company Description: 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. Job Title: IT engineer Data Lakehouse - Tech Lead Job Description: Govern the enterprise-wide standards for data & analytics modeling and performance within the Databricks Lakehouse. * Drive consistency and reuse of core data & analytics artifacts and ensure scalable integration across all business domains. * Provide expert consulting, quality assurance, and enablement for data engineering and data science teams. * Act as a design authority for data warehouse, semantic modeling, and advanced analytics integration. * Acts as the senior engineering point of contact for the lakehouse layer across global teams. * Coordinates with 25+ data engineering and data science professionals across domains and geographies. * Collaborates closely with platform architects, data scientists, governance teams, and functional IT globally. Main Tasks: - Define enterprise 3NF and warehouse modeling standards. - Maintain and review enterprise-wide data & analytics models and shared artifacts. - Align naming conventions and metadata handling with governance standards. - Guide partitioning, indexing, and performance tuning. - Enable, steer and optimize semantic integration with Power BI, live tabular exploration and other tools. - Own common functions, e.G. FX conversion, BOM logic, time-slicing. - Review and approve core components for quality and reusability. - Provide support on high-performance or high-complexity challenges. - Align lakehouse implementation with architectural decisions. - Collaborate with data science and AI teams on model deployment. - Ensure seamless integration of ML/AI pipelines into the lakehouse. - Support LLM and external API integration patterns. - Build and maintain shared libraries and data engineering templates. - Coach junior engineers and define TDD and "as-code" standards. - Drive engineering excellence across the community of practice. - Maintain architectural blueprints, templates, and best practices. - Publish design guidelines and coding standards. - Create re-usable architecture patterns for lakehouse environments. - Monitor usage and implement auto-scaling policies. - Analyze and optimize cluster configurations for cost-efficiency. - Provide cost transparency and usage reporting to stakeholders. Qualifications: Degree in Computer Science or related field; certifications in Databricks or Microsoft preferred. 6–10 years in data engineering with focus on enterprise data & analytics warehouse, lakehouse modeling, and ML integration. Hands-on experience designing large-scale semantic, warehouse, and advanced analytics layers. Track record of architectural ownership and peer enablement with diverse teams. Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.