Data Engineer (Python)

Duration: 3–5 months Location: Armenia, Ukraine, Poland, Estonia

Responsibilities: Shape and contribute to Cargoo’s data engineering strategy, including the design, architecture, and implementation of scalable data solutions Build, maintain, and evolve the Data Platform to support advanced analytics, machine learning, and real-time decision-making Collaborate closely with AI engineers, BI analysts, and business stakeholders to translate data needs into robust technical solutions Identify data opportunities across the organization and enable teams to extract maximum value from data assets Design and implement ETL/ELT pipelines, including batch and streaming data workflows Develop and maintain data models using dimensional and advanced modeling techniques Support deployment, monitoring, and lifecycle management of data applications Apply DataOps best practices to ensure reliability, scalability, and quality of data pipelines Participate in code reviews and promote high engineering standards Take ownership of projects end-to-end, ensuring timely delivery and measurable impact

Requirements: Solid proficiency in Python (runtime environment, package management) and SQL (DML, DDL) Hands-on experience with SQL Server / Azure SQL Server Experience working with cloud platforms, preferably Microsoft Azure Familiarity with the modern data stack, including tools such as dbt and orchestration frameworks (Airflow, Dagster, or similar) Strong understanding of ETL/ELT concepts, data architecture, and data modeling Experience with streaming technologies (Kafka or equivalent) Experience with Docker and container orchestration technologies Experience deploying and monitoring applications on Kubernetes (K8s) Knowledge of application lifecycle management Understanding and application of DataOps practices Strong project management, execution skills, and a clear sense of ownership and accountability