Data Engineer (Databricks)

TL;DR

Data Engineer (Databricks/Azure): Building and optimizing data pipelines and analytical platforms using Python and PySpark with an accent on batch and real-time processing. Focus on designing scalable ETL/ELT pipelines, implementing Data Lakehouse principles via Unity Catalog, and automating workflows in Azure.

Location: Must be based in the European Union (EU) region and possess a valid work permit

Company

hirify.global is a global AI-first digital transformation and engineering partner specializing in scalable data-driven solutions and AI.

What you will do

• Build, maintain, and optimize batch and real-time data pipelines using Python, Databricks, and PySpark.
• Integrate diverse internal and external data sources into an analytical platform.
• Design and implement ETL/ELT pipelines following Data Lakehouse principles and governing assets via Unity Catalog.
• Develop and deploy PyFunc models and manage orchestration using Databricks Workflows.
• Automate data flows with Azure Logic Apps and implement event-driven workflows via Azure Service Bus.
• Collaborate with architects, data scientists, and stakeholders to deliver end-to-end data products.

Requirements

• Minimum 3 years of commercial experience in software or data engineering.
• Strong proficiency in Python and production experience with Databricks and PySpark.
• Practical experience with Azure cloud environments and Azure DevOps (CI/CD).
• Experience with Medallion Architecture and modern data platform design patterns.
• Must be based in the European Union (EU) region and have a valid work permit.
• Experience using AI-powered assistants (e.g., Claude Code, GitHub Copilot, Cursor) to improve productivity.

Nice to have

• Databricks certification.
• Experience with Terraform or ARM templates (IaC).
• Knowledge of MLOps practices and Kubernetes.
• Familiarity with event-driven architectures and distributed processing.
• Experience applying GenAI workflows and prompt patterns within the SDLC.

Culture & Benefits

• People-first culture with a strong emphasis on engineering excellence.
• Opportunity to work with high-profile global clients like Spotify, Disney, and McLaren.
• Environment focused on continuous growth, knowledge sharing, and professional development.
• Exposure to cutting-edge AI-driven development practices.

Hiring process

• CV review followed by an HR introductory call.
• Technical interview.
• Client interview.
• Final decision.