Azure Data Engineer

GeekSoft Consulting

Amsterdam, Netherlands

3 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

careerjet.nl

Tech stack

Agile Methodology Microsoft Azure Big Data Continuous Integration Data Architecture Information Engineering Python (Programming Language) SQL Databases Data Streaming YAML Data Processing Technical Debt

+5 more

Pyspark Infrastructure Automation Frameworks Bicep Data Pipelines Databricks

Job description

Amsterdam, Noord-Holland
Vast
Voltijds
15 uren geleden
Help design, build and continuously improve the clients online platform.
Research, suggest and implement new technology solutions following best practices/standards.
Take responsibility for the resiliency and availability of different products.

Requirements

Experienced Data Engineer with deep expertise in Azure Databricks and Python PySpark to design, build, and maintain robust data processing solutions within a Databricks-centric environment.
Scalable and reliable data engineering practices rather than traditional BI or data enrichment architectures.
Strong hands-on experience managing complex data processing workloads, building maintainable solutions, and making sound technical decisions in a dynamic cloud-based ecosystem.
Strong hands-on experience with Azure Databricks as the core technology platform.
Deep expertise in Python, PySpark, and SQL for large-scale data processing.
Proven experience designing and managing data processing solutions within Databricks environments, including: Streaming and batch data processing, Data modeling and architecture within Databricks, Managing multiple parallel data pipelines on shared source datasets
Strong experience with Azure cloud services and CI/CD pipeline implementation using YAML.
Experience with Infrastructure as Code (IaC) tools such as ARM and Bicep.
Familiarity with Agile methodologies and collaborative development practices.
Broader understanding of end-to-end enterprise data solutions and modern data architectures.
Strong focus on quality, reliability, scalability, and maintainability while minimizing technical debt.
Proactive and improvement-driven mindset with a passion for engineering excellence.
Excellent collaboration and communication skills across technical and business teams.
Structured and pragmatic approach to solution design, with emphasis on practical engineering over unnecessary complexity or over-engineering.