Job description
We are looking for a motivated and skilled Data Engineer with a solid foundation in data pipeline development, geospatial data handling, and optimization algorithms. This role involves working with cutting-edge technologies including 3D simulation platforms, real-time data integration, and advanced optimization tools. You will contribute to the design, implementation, and optimization of data-driven solutions within simulation environments. The ideal candidate is passionate about technology, eager to work on innovative projects, and capable of collaborating across multidisciplinary teams.
Requirements
- 1 to 3 years of experience in data engineering, with exposure to geospatial data and optimization algorithms.
- Proficiency in Python and SQL.
- Experience with Apache Spark and Databricks.
- Familiarity with 3D simulation platforms is highly desirable.
- Knowledge of optimization tools such as CuOpt, Gurobi, or CPLEX.
- Experience with cloud platforms (AWS, Azure) and scalable data architectures.
- Strong analytical and problem-solving abilities.
- Good communication and teamwork skills.
- Fluent English is mandatory.
Responsibilities
- Design, develop, and maintain data pipelines supporting geospatial and optimization workflows.
- Integrate data sources such as Apache Kafka, S3, and others into simulation environments.
- Develop and optimize real-time pipelines using tools like Apache Spark and Databricks.
- Implement and customize optimization algorithms or modules (e.g., CuOpt, Gurobi, CPLEX) for enhanced system performance.
- Collaborate with cross-functional teams including data scientists and engineers to deliver impactful simulation and decision-making tools.
- Analyze and improve the performance and scalability of systems and algorithms.
- Work with cloud platforms (AWS, Azure) to deploy and manage data and optimization solutions.
- Maintain geospatial databases using tools like PostGIS and ArcGIS.
