Senior/ medior data engineer

REQUIREMENTS AND QUALIFICATIONS

Job requirements include:

• Good proficiency in English (mandatory) - B2/C1
• At least 3 years of relevant experience as a Data Engineer or in a similar role
• Strong experience designing and implementing ETL/ELT pipelines using Python
• Experience extracting and integrating data from REST APIs
• Strong SQL skills and experience with data modeling
• Ability to translate business requirements into data models, KPI definitions, and dashboard specifications
• Experience building and publishing Power BI dashboards and reports
• Familiarity with Microsoft Fabric (e.g., Lakehouses, Data Factory, Pipelines)
• Understanding of Azure data services (e.g., Azure SQL, Data Lake, Storage)
• Experience working in Agile/Scrum environments
• Strong analytical and problem-solving skills
• Taking ownership of tasks and delivering high-quality solutions
• Excellent communication and teamwork skills
• Attention to detail and a passion for quality

As a (Mid/Senior) Data Engineer, you work closely with the development and DevOps teams to enable data-driven decision making across the platform, while maintaining high quality, scalability, and reliability standards. You bring strong Python and SQL skills, a solid understanding of the Microsoft data ecosystem, and a drive to design clean, maintainable, and production-ready data solutions.

You are responsible for designing and implementing robust ETL/ELT pipelines, translating business requirements into scalable data models and KPI definitions, and collaborating with customers and internal teams to deliver reliable dashboards and analytics solutions.

Your work includes extracting data from cloud and on-premise applications via REST APIs using Python, transforming and loading it into SQL databases or lakehouse environments, and visualizing customer-requested KPIs in Power BI dashboards.

In addition, you contribute to the design and oversight of data environments anchored in Microsoft Fabric and Azure. This includes ensuring performance, maintainability, cost-efficiency, and proper integration within the broader cloud architecture. You collaborate with DevOps teams to implement CI/CD practices for data pipelines and ensure production-grade deployment standards.