Working Student Data Engineering

Beschreibung

Job Zusammenfassung In dieser Rolle unterstützt du das Vendor Data Team, indem du Datenpipelines für die Vendor Sales & Operations optimierst, SQL- und dbt-Modelle entwickelst und die Datenqualität über Tools wie Monte Carlo sicherstellst. Job Zusammenfassung In dieser Rolle unterstützt du das Vendor Data Team, indem du Datenpipelines für die Vendor Sales & Operations optimierst, SQL- und dbt-Modelle entwickelst und die Datenqualität über Tools wie Monte Carlo sicherstellst. Deine Rolle im Team We are on the look out for a Working Student, Data Engineering for our Vendor Data Team, where your work will directly support how vendors are discovered, managed, and analyzed at scale. You'll be working mostly on Vendor Sales & Operations topics, contributing to data-driven initiatives such as vendor lead generation, vendor management, and competitor analysis. As part of our Vendor Team, you'll be the driving force behind the success of thousands of restaurants, shops, and local businesses. Your contributions will empower vendors with advanced tools to manage their operations, boosting their visibility and reach. Every feature you help build will create growth opportunities for businesses of all sizes, strengthening Delivery Hero's ecosystem and impact. This is a hands-on role designed for students who want real production exposure. You'll work with modern data tooling and collaborate closely with data engineers, analytics engineers, and business stakeholders. Support the maintenance and improvement of data ingestion and transformation pipelines powering Vendor Sales & Operations use cases. Work with SQL and dbt to build, test, and optimize data models in BigQuery. Help monitor and ensure data quality and reliability using tools like Monte Carlo. Assist with Airflow-based orchestration, debugging pipeline failures and improving robustness. Contribute to ML matching systems by supporting data preparation, validation, and monitoring. Collaborate closely with data engineers, analysts, and commercial stakeholders to understand data needs and translate them into reliable datasets. Document data models, pipelines, and assumptions to improve transparency and long-term maintainability. Unsere Erwartungen an dich Qualifikationen You are currently enrolled in a Bachelor's or Master's program such as: Computer Science, Computer Engineering, Software Engineering. Strong working knowledge of SQL and Python (this is essential). Basic understanding of data pipelines, ETL/ELT concepts, and analytical data modeling. A proactive and communicative mindset - you ask questions, flag issues early, and enjoy collaborating with others. Eagerness to learn, take ownership of tasks, and grow your technical skills in a production environment. Ability to work independently in a remote-friendly setup, while joining on-site twice per week. Exposure to data quality or observability tools (e.g., Monte Carlo) is nice to have. Basic understanding of machine learning pipelines or matching systems is nice to have. Interest in vendor ecosystems, marketplaces, or competitive intelligence is nice to have. Erfahrung Familiarity or hands-on experience with dbt and modern data warehouses (BigQuery is a plus). Prior experience with Airflow or other workflow orchestration tools is nice to have. Benefits Essen & Trinken 🍏 Frisches Obst 🥪 Snacks, Süßigkeiten Work-Life-Integration 🧳 Relocation Package 🏠 Home Office ⏰ Flexible Arbeitszeiten 🍼 Kinderbetreuung Gesundheit, Fitness & Fun 🎳 Team Events 🧘‍♀️ Massage, Yoga o. A. Themen mit denen du dich im Job beschäftigst AI Data Economy Metadaten Level: Junior Job Feld: Data Anstellung: Teilzeit Vertragsart: Praktikum / Schulpraktikum Arbeitsmodell: Hybrid, Onsite Unternehmenstyp: Etablierte Firma Branche: Handel Ort: Berlin | Deutschland

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