Data Engineer

• Design, build, and maintain scalable analytical data platforms and pipelines using Python and SQL;
• Own and continuously improve data modeling practices, leveraging tools such as dbt to ensure data quality, consistency, and usability;
• Develop, maintain, and optimize ETL/ELT processes to support reliable and timely data ingestion and transformation;
• Design and manage data warehouse solutions, including hands-on work with Snowflake (architecture, performance tuning, and cost optimization);
• Work with relational databases (e.g., PostgreSQL), ensuring robust database design and efficient querying;
• Collaborate closely with engineering, product, and analytics teams to understand data requirements and translate them into scalable data solutions;
• Contribute to the design and operation of cloud-based data infrastructure, preferably within the Azure data ecosystem (Data Lake, Databricks, Data Factory);
• Monitor, troubleshoot, and improve data pipelines and platform reliability in production environments;
• Support integration of data platforms with microservices and APIs, ensuring seamless data flow across systems;
• Work with streaming and real-time data technologies such as Kafka and Flink;
• Support deployment and operationalization of machine learning and AI models within the data platform., * During the interview (about 30 min), our HR specialist will discuss your expected career goals, experience, and your expectations from the company. We will also check your level of English.
• The technical interview (about 1 hour) will be conducted by our team lead. Depending on the position, we may also present a spontaneous challenge to solve.
• Upon successful interview completion, you will receive a formal job offer. It will outline the details of the position, including the agreed-upon terms, salary, benefits, and other relevant information.

Do you have experience in Security?, SoftTeco is looking for a highly skilled Data Engineer to join a dynamic international project in the healthcare domain.

We are developing a patient engagement platform for clinical trials, where human-supervised AI transforms unstructured patient criteria into structured data, enabling efficient and accurate matching of patient profiles with clinical trials.

The ideal candidate should have deep hands-on experience, a collaborative mindset, and strong enthusiasm for data engineering in cloud environments., * 5-10 years of experience as a Data Platform Engineer, Data Engineer, or Analytics Engineer;

• Strong proficiency in Python and SQL;
• Experience owning, maintaining, and improving analytical data modeling practices using tools such as dbt;
• Experience owning, maintaining, and improving ETL/ELT processes;
• Ideally, 1-2 years of hands-on, production-grade experience with Snowflake, including architecture design, query performance optimization, and cost monitoring;
• Strong database knowledge, including database design and programming (e.g., PostgreSQL);
• Practical knowledge of the Azure data stack is highly beneficial (Azure Data Lake, Databricks, Azure Data Factory, etc.);
• Familiarity with microservices architecture and related technologies, such as Kubernetes, Docker, and REST APIs;
• Proficiency in Apache Kafka and Apache Flink;
• Experience developing and deploying machine learning and AI models., * Excellent English language skills (both written and verbal, minimum B2 level);
• Strong analytical thinking to understand complex data requirements, troubleshoot issues, and optimize data processes;
• Effective communication skills to collaborate with cross-functional teams, translate technical concepts, and manage stakeholder expectations;
• Proven ability to work independently and within agile teams, balancing priorities and meeting deadlines;
• Experience in cloud data environments and familiarity with data governance and security best practices is a plus.