Data Science Engineer (Python)

3-5+ years of work experience in software engineering, with a focus on data engineering, ML engineering, or data-intensive applications. Expert proficiency in Python, with strong object-oriented design and software system design skills. Hands-on experience with large-scale data processing tools like Apache Spark (PySpark) or Dask. Solid experience with cloud platforms, preferably GCP, including deployment, management, and scaling (Docker, Cloud Run, GKE). Experience with large data systems on GCP (Dataproc, BigQuery). Strong SQL skills and experience with large, complex datasets. Deep understanding of machine learning concepts, the model development lifecycle, and MLOps principles. Excellent problem-solving skills for distributed systems and performance optimization. Clear and effective communication of technical ideas and design decisions in English. Advanced English proficiency (B2-C1) with excellent communication, teamwork, and consulting skills.

Design, develop, test, and maintain scalable data pipelines using Python and large-scale data processing tools. Design and own key parts of ML systems, ensuring reliability and scalability. Set up and manage MLOps practices, including CI/CD, model monitoring, and automated launches. Improve and manage data processing jobs on GCP platforms (Dataproc, BigQuery, Cloud Run, Cloud Build). Work with data scientists to productionize machine learning models and integrate them with data systems. Write detailed documentation for system designs, code, and managed systems. Troubleshoot complex technical issues in distributed data systems and ML pipelines.