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Data Engineer (Azure)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Data Engineer (Azure/PySpark): Building and scaling an enterprise data platform to support analytics and AI-enabled use cases with an accent on reliable data pipelines and Azure integration. Focus on implementing SQL- and Spark-based transformations and optimizing production data workflows.

Location: Hybrid (3 days on site in London, England)

Company

hirify.global Data Centers provides high-scale data center infrastructure for hyperscalers and cloud providers globally.

What you will do

  • Design and maintain scalable data pipelines using Python and PySpark on the Microsoft Azure platform.
  • Develop batch and incremental pipelines using Azure Data Factory and Azure Data Lake Storage Gen2.
  • Implement SQL and Spark-based transformations to produce curated datasets for reporting and analytics.
  • Take ownership of pipeline monitoring, troubleshooting, and performance optimization in production.
  • Collaborate with business analysts and stakeholders to translate requirements into technical data solutions.
  • Structure and prepare data to support advanced analytics and AI-enabled use cases.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Data Analytics, or equivalent experience.
  • 3–5 years of experience in data or analytics engineering.
  • Proficiency in Python (including PySpark) and SQL.
  • Experience building solutions on Azure (Data Factory, Synapse, Data Lake Storage Gen2).
  • Experience with Git and CI/CD workflows using GitHub or Azure DevOps.
  • Strong understanding of data modeling fundamentals (fact and dimension tables).

Nice to have

  • Experience with distributed data processing frameworks like Apache Spark.
  • Exposure to preparing data for machine learning or intelligent applications.
  • Familiarity with Azure Functions or Logic Apps.
  • Experience supporting data platform refactoring or modernization initiatives.

Culture & Benefits

  • Competitive total compensation package.
  • Comprehensive health, welfare, and retirement benefits exceeding local expectations.
  • Flexible work policy supporting a hybrid environment.
  • Culture based on "No Ego and No Arrogance" with a focus on mutual support and respect.

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