Если вы раньше входили через Google, сбросьте пароль для своей Gmail-почты через кнопку «Забыли пароль?» на экране входа. Затем войдите по email и новому паролю.
Если аккаунта ещё нет, зарегистрируйтесь с Gmail-почтой, после подтверждения почты мы предложим задать пароль.
Что нового
Загружаю обновления...
Что нового
Загружаю обновления...
Работа найдется быстрее с подпискойКандидат найдётся быстрее с подпиской
Чтобы адаптировать резюме под вакансию или составить сопроводительное письмо, загрузите резюме
описание
Please take a moment to read it and check the boxes before submitting your application. I agree to the processing of my personal data by Vention Development sp. z o.o. with its registered office in Lodz (Poland) in the scope of future recruitment processes per Applicant Information Clause. I agree to receive from Vention Development sp. z o.o. with its registered office in Lodz (Poland), via e-mail, information about Vention news and events.
Vention is a global engineering partner to tech leaders and fast-growing startups, combining product development expertise with an AI-first approach. It helps startups and enterprises turn data into smart decisions and better user experiences by building scalable data pipelines and infrastructure.
задачи
Build, optimize, and maintain scalable ETL/ELT pipelines using cloud platforms;
Integrate and manage diverse data sources, ensuring data quality, reliability, and accessibility for analytics and ML use cases;
Design and maintain cloud-native data architectures, including Data Lake, Data Warehouse, and Data Lakehouse;
Develop data processing solutions using Spark and PySpark in distributed environments;
Collaborate with cross-functional teams to translate business requirements into efficient, scalable data solutions;
Support analytics use cases by enabling data consumption for reporting, dashboards, and visualization tools;
Stay up to date with modern data platform technologies and best practices, contributing to continuous improvement of the data ecosystem.
требования
4+ Years of experience in Data Engineering, delivering end-to-end data solutions;
Strong hands-on experience with Python and SQL;
Solid expertise with Apache Spark and PySpark for distributed data processing;
Hands-on experience with AWS, including Glue, S3, Athena, and QuickSight, or Azure, including Data Factory, Databricks, and ADLS;
Good understanding of modern data architectures, including Data Lake, Delta Lake, and Data Warehouse;
Experience working in an Agile environment, such as Scrum or Kanban;
English B2+, comfortable communicating with English-speaking customers.
условия
Salary from 10000 PLN gross;
EDU corporate community with tech communities, interest clubs, events, an R&D lab, a knowledge base, and a dedicated AI track;
Licenses for AI tools, including GitHub Copilot and Cursor;
Private medical care with LuxMed;
Kafeteria MyBenefit credits for stores, restaurants, and cafés;