Data Engineer II at SIXT

The central Business Intelligence team builds and maintains the SIXT Data Platform and its Data Catalogue, serving thousands of users globally. Our flagship product, the SIXT Data Shop, ingests tens of millions of events daily, processes them to meet diverse consumer needs, and delivers insights through a comprehensive toolbox—from self-service batch processes to real-time ML model endpoints. Our current focus areas include advancing operational automation, expanding self-service capabilities for data ingestion, ETL workflows, and distribution, and enabling innovative use cases for our customers. Our team of Data Engineers and Business Intelligence Engineers is hands-on, collaborative, and constantly exploring cutting-edge technologies. If you want to be part of our journey and make an impact. Apply now! YOUR ROLE AT SIXT • You explore and implement the latest AWS and big data technologies to uncover hidden opportunities, enable new capabilities, and build integrations for the SIXT Data Shop • You collaborate Cross-Functionally: Partner with Data Engineers, BI Analysts, and Data Scientists to architect optimal solutions for diverse analytical use cases, including dashboarding, ad hoc analytics, data-as-a-product, and machine learning • You contribute to the Data Platform vision and roadmap through your expertise, innovative ideas, and intellectual curiosity • You demonstrate exceptional work ethics and integrity when handling sensitive customer data, maintaining the highest standards of data protectionYOUR SKILLS MATTER • You have B.Tech/B.E/ Master’s Degree in Computer Science or similar discipline • You have atleast 3+ years of professional experience as Data Engineer • You have experience with hybrid Data Lake and Data Warehouse architectures, including end-to-end automation of data models from source systems to analytical dashboards using ELT methodologies • You have expertise with analytical cloud data warehouses (Redshift, Snowflake), data transformation using dbt, and orchestrating interdependent workflows with Apache Airflow • You have hands-on experience with AI coding assistants and agentic workflow automation. Ability to leverage LLMs with contextual data and RAG (Retrieval-Augmented Generation) systems • You have strong foundation in engineering best practices throughout the development lifecycle, including agile methodologies, code reviews, source control (GitHub), CI/CD pipelines (Jenkins), testing, and operations. Deep understanding of data management fundamentals, distributed systems, and data storage/compute principles • You have advanced proficiency in Python and SQL