Design, develop, and maintain Python-based ETL pipelines for infrastructure and capacity data
Implement robust data access layers using SQLAlchemy and psycopg2
Integrate with monitoring and metrics systems (Prometheus / VictoriaMetrics) and inventory sources (NetBox)
Develop aggregation and normalization logic for capacity data across regions and node types
Persist and manage historical datasets in PostgreSQL
Collaborate with Data Engineers and stakeholders to define forecasting and reporting requirements
Improve reliability, performance, and maintainability of automated pipelines
Replace manual, Excel-based workflows with scalable, auditable, automated solutions

At least 5 years of professional experience in Python development, including data processing and automation
Strong hands-on experience with SQLAlchemy and psycopg2 for building and maintaining database interaction layers
Solid background in working with SQL and relational databases, preferably PostgreSQL
Practical experience with monitoring and metrics systems such as Prometheus or VictoriaMetrics
Proven ability to take ownership of solutions from design through to production delivery
Excellent communication skills for collaboration with both technical and non-technical stakeholders
Upper-Intermediate level of English

WILL BE A PLUS:

Experience with data visualization tools such as Grafana, Kibana, or PowerBI
Familiarity with NetBox or other CMDB/inventory management tools
Knowledge of storage systems, capacity planning, or infrastructure lifecycle management
Background in working with time-series data or forecasting-related solutions
Proven track record in designing or maintaining ETL pipelines in production environments
Understanding of data aggregation, normalization, and historical tracking processes
Experience with cloud or hybrid infrastructure environments

PERSONAL PROFILE:

Senior Software Developer (Cloud Data & Automation)

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