Senior Data Engineer

Minimum 7 years of experience in Data EngineeringStrong background in designing and implementing scalable data processing systems (pipelines, ETL processes, data warehouses, and data lakes)Hands-on experience with implementing data warehousing solutions like Snowflake, Databricks or Apache IcebergStrong background and at least 3 years of hands on experience in either AWS or Azure data engineering servicesPractical experience with dbt for data transformationStrong SQL skills and experience with relational databasesFamiliarity with Apache Airflow for workflow orchestrationProficiency in Python for data engineering tasksStrong problem-solving and analytical thinking abilitiesVery good communication skills in English (min. B2 level)AI native mindset At STX Next, Data Engineers are creative problem-solvers who thrive at the intersection of data, innovation, and technology. Our approach to challenges is both collaborative and inventive, driven by the belief that every obstacle has a solution. You’ll join a dedicated team that transforms data into valuable systems, addressing clients' needs and elevating the experience for end users.As a Data Engineer, you’ll work closely with international clients, providing both consultancy and technical architecture to shape reliable, high-performance data solutions. You’ll handle everything from large data sets to distributed systems, setting a high bar for data quality. If you’re excited by complex problems and want to contribute to a collaborative culture of craftsmanship, STX Next offers the platform to bring your ideas to life. ,[Develop innovative solutions for complex data challenges, using creativity and technology., Design and build data systems that fulfill client requirements and optimize user experience., Collaborate across teams to integrate unique approaches and out-of-the-box thinking into problem-solving., Serve as a trusted consultant and architect for customized data solutions for global clients., Handle large-scale data processing and manage distributed systems to ensure reliability and performance., Uphold high standards of data quality and refine approaches to align with best practices., Foster a culture of collaboration, craftsmanship, and continuous improvement.] Requirements: Python, SQL, Data engineering, AWS, Azure, dbt, Apache Airflow, Snowflake, Databricks, Apache Iceberg, English