Data Engineer (Azure)

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.