Вакансия Senior Data Engineer

1 вакансия
Специализация: Python
Уровень: Senior
Опыт: 4 года
Уровень английского: Upper-Intermediate
Город: Минск
Режим работы: Полный день
Размер команды: 3—5
Размер компании: 65
Возможна удалённая работа: Да

Craft is looking for an experienced and motivated Data Engineer to join a team responsible for a key product within the organisation. As a core member of this team, you will have a great say in how solutions are engineered and delivered.

Craft gives engineers a lot of responsibility, which is matched by our investment in their growth and development. We are growing quickly, and the only limits to your future growth with Craft are your interests and abilities.

Responsibilities will include:

  • Building and optimising data pipelines (batch & streaming) for big data systems.
  • Extracting, Analysing and Modelling of rich & diverse data sets.
  • Applying Data mining to techniques such as anomaly detection, clustering, regression, classification, summarisation to extract value from our data sets.
  • Ensuring data analysis is in line with company policies and regulations.
  • Strong problem solving and the ability to communicate ideas effectively.
  • Support Data Engineering Lead in setting Data Strategies and vision.
  • Keep track of emerging technologies & trends in the Data Engineering world, incorporating modern tooling and best practices at Craft.
  • Coach and mentor other Data Engineers by providing leadership and regular feedback.
  • Work on extendable data processing system that allows to add and scale pipelines with low-code approach
  • Constantly review performance, infrastructure and deliverables of other engineering teams to help them improve

We'd love to hear from you if

  • Show curiosity through asking questions, digging into to new technologies, and always trying to grow.
  • 5+ years of experience in Data Engineering.
  • 5+ years of experience with Python
  • Knowledge and experience of Amazon Web Services (AWS).
  • Experience using Terraform or other infrastructure-as-code tools.
  • Self-starter, independent, likes to take initiative.
  • Have fundamental and deep knowledge of data engineering techniques: ETL (Batch & Streaming), DWH, Data Lakes, MPP
  • Data analytical and statistical background would be a large plus
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