carVertical
carVertical
carVertical — avtomobil tarixini baholashni osonlashtirishga e’tibor qaratadigan avtomobil ma’lumotlari kompaniyasi. Uning VIN asosidagi hisobotlari sug‘urta, politsiya, ro‘yxatdan o‘tkazish va ta’mirlash qaydlari kabi 1 000 dan ortiq manbalardan olingan ma’lumotlarni birlashtiradi. Bu hisobotlar foydalanilgan avtomobil xaridorlari va sotuvchilariga ehtimoliy shikastlanishlar, yurish masofasidagi tafovutlar, hujjatlarga oid muammolar, avtomobil xususiyatlari, xavfsizlik reytinglari hamda bozor narxlari taqqoslovini ko‘rib chiqishda yordam beradi. Kompaniya shuningdek mobil ilovalar va dilerlar, sug‘urta kompaniyalari hamda lizing kompaniyalari uchun API integratsiyalari kabi biznes yechimlarini taqdim etadi.

Senior Data Engineer in Vilnius (Hybrid) at carVertical

Build scalable data pipelines and platforms at carVertical, using automotive data to improve how vehicles are bought, owned, and traded. Drive architecture, infrastructure, and engineering standards across the data platform.

Tavsif

  • Create scalable data pipelines and robust data models
  • Strengthen the infrastructure that supports data solutions
  • Investigate and experiment to solve complex data engineering problems
  • Partner with data, AI, machine learning, and intelligence teams
  • Own technical and architectural decisions for the data platform
  • Establish standards for testing, code quality, and infrastructure
  • Find and address technical debt
  • Improve infrastructure performance and manage costs effectively
  • Lead technical discussions and constructively question existing approaches
  • Share expertise and help fellow engineers grow
  • Work with Data Department teams to resolve dependencies and improve data flow

Talablar

  • Demonstrated experience building and maintaining production-grade data pipelines and data warehouse solutions
  • Strong knowledge of scalable, reliable, and maintainable data architecture
  • Practical experience with modern cloud data platforms and infrastructure
  • Regular experience using AI coding assistants and agents in engineering work
  • Experience with or familiarity with BigQuery, AWS, Terraform, dbt, Airflow, Spark, and AI agents
  • Sound understanding of software engineering practices
  • Ability to navigate ambiguous technical problems and make well-reasoned decisions
  • Strong collaboration skills across multiple technical teams

Imtiyozlar

  • Choose to work from home, the office, or a combination of both
  • Flexible working hours
  • Meaningful ownership of complex technical challenges
  • Learn from experienced colleagues while developing technical and leadership skills
  • Use a modern data stack with access to AI development tools
  • Help shape and improve the use of AI development tools

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