In Cyclad We work with top international IT companies to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We are seeking an experienced Azure Data Engineer with Databricks expertise to join a remote development team. The role focuses on designing, building, and maintaining scalable, cloud-based data platforms using the Microsoft Azure analytics stack and modern Databricks features. The candidate will collaborate closely with architects, data scientists, and business stakeholders to deliver secure, production-ready data solutions.

Project information:

• Type of project: IT services
• Office location: Poland
• Work model: Remote
• Budget: 150-180 PLN net /h - b2b
• Project length: Longterm
• Only candidates with citizenship in the European Union and residence in Poland
• Start date: ASAP (depending on candidate's availability)

Project scope:

• Design, build, and deploy scalable data pipelines using Azure Databricks and the Azure Analytics stack
• Curate structured, semi-structured, and unstructured data by creating efficient, cost-effective, and scalable pipelines
• Create and maintain robust data pipeline architecture ensuring data quality, reliability, and scalability
• Assemble and manage large, complex datasets to meet functional and non-functional business requirements
• Identify, design, and implement process improvements, including automation and optimization of data delivery
• Work with real-time and streaming analytics solutions where applicable
• Collaborate closely with Product Owners, Scrum Masters, architects, and data leadership to ensure timely, high-quality delivery
• Align with Data Engineering chapter standards, processes, and best practices
• Apply solid software engineering practices, including unit testing, CI/CD, and version control
• Troubleshoot complex data-related issues and perform root cause analysis
• Ensure data security, governance, and compliance with data management frameworks

Tech Stack:

• Cloud: Microsoft Azure (Data Factory, Event Hubs, CosmosDB, Databricks)
• Data Processing & Analytics: Databricks, Spark, SQL, real-time analytics tools
• Programming & Scripting: Python, SQL
• DevOps & CI/CD: Git, CI/CD pipelines, unit testing
• Workflow & Orchestration: Airflow
• Data Management & Governance: Data modelling, Collibra/Alation (optional), DAMA frameworks