29 сен

Data Engineer

ориентир по рынку
вакансия зп не указана
в среднем 205 459 ₽
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Рекламный баннер: ОБЩЕСТВО С ОГРАНИЧЕННОЙ ОТВЕТСТВЕННОСТЬЮ "ЦЕНТР НАЦИОНАЛЬНЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ"
О рекламодателе
ОБЩЕСТВО С ОГРАНИЧЕННОЙ ОТВЕТСТВЕННОСТЬЮ "ЦЕНТР НАЦИОНАЛЬНЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ"
ИНН: 9704271170

описание

Accepting applications until:

16 October 2026

задачи

A hands-on role building scalable data infrastructure that powers AI-driven products and audience intelligence.

  • Data Platform & Pipeline Engineering (60%): Design, build and maintain scalable batch and near real-time pipelines across ingestion, transformation and serving layers. Develop reusable data models and optimise performance, reliability and cost.
  • Platform Evolution & Engineering Excellence (20%): Shape the Global:IQ data platform through best practices in architecture, tooling, CI/CD and infrastructure as code. Create reusable components and maintain clear technical documentation.
  • Quality & Governance (10%): Implement robust data validation, testing, lineage and observability to ensure high-quality, trusted datasets. Support governance and privacy-conscious data handling.
  • Collaboration & Enablement (10%): Partner with Data Science, MLOps, Product and commercial teams to deliver production-ready data solutions. Support and mentor others while communicating clearly with stakeholders.
  • Developed a strong understanding of the Global:IQ platform and its core use cases
  • Successfully onboarded key datasets with robust ingestion and quality standards
  • Delivered reliable pipelines supporting live production use cases
  • Established or improved data engineering standards and best practices
  • Built strong working relationships across Data, Product and commercial teams
  • Identified opportunities to improve scalability, reliability and efficiency
  • требования

    • Programming & Data Skills: Strong Python and SQL skills, with experience building production-grade data pipelines
    • Data Platform Experience: Hands-on experience with modern data tools (e.g. Snowflake, Airflow, dbt) and cloud environments (preferably AWS)
    • Engineering Best Practice: Knowledge of CI/CD, testing, version control and infrastructure as code
    • Data Quality & Governance: Understanding of observability, validation and maintaining reliable data systems
    • Collaboration & Communication: Ability to translate business and data science needs into scalable solutions and communicate clearly with stakeholders
    • Mindset & Approach: Pragmatic, ownership-driven and curious, with a passion for building impactful data products

    условия

    Think Big: Build a data platform from the ground up that will scale with a cutting-edge AI and ML product.

    Own It: Take responsibility for production-grade data systems that directly power targeting, optimisation and measurement.

    Keep it Simple: Apply pragmatic engineering to deliver reliable, maintainable solutions without over-engineering.

    Better Together: Work in a highly collaborative, cross-functional team spanning technical and commercial expertise.

    Если просят выйти из iCloud, прислать код из SMS, запустить или установить что-то, перевести деньги — не соглашайся: это мошенничество.

    Спроси Хайрика про вакансию

    Сверит с твоим резюме, подскажет вилку и вопросы на собесе.

    Если просят выйти из iCloud, прислать код из SMS, запустить или установить что-то, перевести деньги — не соглашайся: это мошенничество.