Responsibilities

• Design, develop, and optimize data models.
• Build and maintain databases, data warehouses, and data processing and storage systems.
• Create and manage ETL/ELT processes.
• Clean, transform, and process data to ensure quality, consistency and compliance with business requirements.
• Create scripts and procedures to automate processes.
• Test data quality.
• Collaborate with analytics and business teams to understand requirements and deliver data in the right format and at the right time.
• Develop and maintain documentation on data infrastructure, ETL/ELT processes, database schemas, and other data management aspects.
• Work with partners from other countries; travel to other countries.

Requirements

• Higher education in Computer Science, Mathematics/Statistics, Telecommunications or related field.
• Ability to work with large data volumes in an operational environment.
• Experience in data engineering for AI/ML solutions hosted on-prem or in the cloud (GCP preferred).
• Experience in Data Warehousing and Business Intelligence.
• Strong knowledge of Python libraries and frameworks (Pandas, FastAPI, Kubeflow Pipelines, GCP libraries).
• -

Responsibilities

• Design, develop, and optimize data models.
• Build and maintain databases, data warehouses, and data processing and storage systems.
• Create and manage ETL/ELT processes.
• Clean, transform, and process data to ensure quality, consistency and compliance with business requirements.
• Create scripts and procedures to automate processes.
• Test data quality.
• Collaborate with analytics and business teams to understand requirements and deliver data in the right format and at the right time.
• Develop and maintain documentation on data infrastructure, ETL/ELT processes, database schemas, and other data management aspects.
• Work with partners from other countries; travel to other countries.

Requirements

• Higher education in Computer Science, Mathematics/Statistics, Telecommunications or related field.
• Ability to work with large data volumes in an operational environment.
• Experience in data engineering for AI/ML solutions hosted on-prem or in the cloud (GCP preferred).
• Experience in Data Warehousing and Business Intelligence.
• Strong knowledge of Python libraries and frameworks (Pandas, FastAPI, Kubeflow Pipelines, GCP libraries).
• -

Правовое

• Конфиденциальность
• Условия
• Cookies

Правовое

• Конфиденциальность
• Условия
• Cookies