Senior Azure Data Engineer (Databricks)

TL;DR

Senior Azure Data Engineer (Azure/Databricks): Designing, building, and maintaining scalable data pipelines supporting analytics, reporting, and AI/ML use cases with an accent on Databricks, Spark, and medallion architecture. Focus on optimizing data ingestion workflows, implementing robust CI/CD practices for data platforms, and ensuring high data quality and reliability.

Location: Work from the European Union region and a work permit are required

Company

hirify.global is a global AI-first digital transformation and engineering partner specializing in AI, Data, and Cloud solutions for high-profile clients.

What you will do

• Design and maintain scalable data pipelines for analytics, reporting, and AI/ML use cases.
• Develop and optimize data ingestion and transformation workflows across multiple source systems.
• Implement data models using layered/medallion-style architectures to support consumption patterns.
• Build production pipelines using Databricks notebooks integrated with orchestration and CI/CD tools.
• Ensure data quality, reliability, and performance through testing, monitoring, and validation.
• Collaborate with analytics, product, and engineering teams to align data solutions with business needs.

Requirements

• Solid experience in data engineering with strong proficiency in Python and SQL.
• Hands-on experience with Spark, PySpark, and developing pipelines in Databricks.
• Proficiency with Azure DevOps for CI/CD and Azure Data Factory (ADF) for orchestration.
• Solid understanding of ETL/ELT design, data modeling, and lakehouse patterns.
• Experience working in a structured SDLC environment with version control.
• Must be based in the European Union region and possess a valid work permit.

Nice to have

• Familiarity with Databricks ecosystem features and recent platform capabilities.
• Experience with data platform governance tools such as cataloging and lineage.
• Awareness of feature stores, data apps, and conversational analytics.
• Basic understanding of machine learning workflows.

Culture & Benefits

• People-first culture with a strong emphasis on engineering excellence.
• Consulting mindset with a continuous focus on growth and knowledge sharing.
• Opportunity to work with leading global brands like Spotify, Disney, and McLaren.
• AI-first approach to digital transformation and engineering.

Hiring process

• CV review and HR introductory call.
• Technical interview.
• Client interview and final decision.