Middle Data Engineer

• Design and develop scalable, reliable data platforms and pipelines for analytics and operations
• Implement data processing workflows using distributed frameworks such as Apache Spark/pySpark and Databricks
• Evolve the organization's cloud data platform using Azure technologies, including Data Factory, Synapse, Event Hub, and Azure Data Lake Storage
• Model data to support analytics, reporting, and downstream consumption
• Integrate and process data from multiple sources while ensuring quality and consistency
• Monitor and optimize pipeline performance, reliability, and scalability
• Collaborate with analysts, scientists, and engineers to translate requirements into solutions
• Improve data engineering standards, testing, and operational reliability
• Evaluate and introduce new tools and technologies in the data engineering ecosystem

• 4+ years of hands-on experience in data engineering or building data processing platforms
• Strong SQL skills
• Solid Python experience for pipeline development
• Experience with distributed processing frameworks, including Apache Spark/pySpark; Databricks preferred
• Practical experience designing and implementing pipelines in cloud environments; Azure preferred
• Experience with production-scale analytical systems and data modeling
• Understanding of ETL/ELT design, dimensional modeling, and data warehousing principles
• Experience with modern data lake architectures and formats, including Parquet and JSON
• Familiarity with workflow orchestration tools, including Airflow
• Experience with database development and optimization
• Ability to design scalable solutions with minimal supervision
• Strong collaboration and communication skills
• Professional proficiency in English

• Professional growth opportunities
• Supportive environment
• Competitive benefits
• Remote work option