Arina Goloubitskaya (CV)

Software Engineer | Python Backend & Data Science
Minsk, Belarus · +375 44 767 6187 · arinaogo@gmail.com · Telegram: @sweetd0ve

Summary

Backend Software Engineer with 3+ years of commercial experience building reliable, scalable, and maintainable backend systems. Computer Science graduate (HSE University, Moscow) with strong foundations in software engineering and applied ML. Proficient across the Python backend stack (FastAPI / Django / Flask): API design, database-driven services, integration patterns, and engineering excellence (clean architecture, testability, readable code). Hands-on with Data Science / ML tooling (PyTorch, TensorFlow) for building training/inference workflows and production-oriented pipelines. Consistently delivers high-quality results under deadlines.
Languages: Russian (Native), English (B2).

Technical Skills

• Backend Engineering (Python)
  • RESTful API design (OpenAPI/Swagger), request validation, versioning, pagination
  • Service-layer architecture, domain modeling, DTO/ORM mapping, background jobs
  • Integrations with external systems (webhooks, third-party APIs), retries, idempotency
  • Observability: structured logging, metrics, tracing; operational debugging
• Frameworks
  • FastAPI (async endpoints, dependency injection, background tasks)
  • Django (ORM, admin, app architecture, middleware)
  • Flask (lightweight services, extensions, blueprints)
  • Streamlit (data apps, rapid prototyping, internal tooling)
• Databases & ORM
  • PostgreSQL (schema design, indexing basics, query performance tuning mindset)
  • SQLAlchemy (ORM/data-mapper patterns, migrations-minded workflows)
• Data & Machine Learning
  • Machine Learning: feature engineering basics, evaluation metrics, reproducible experiments
  • PyTorch, TensorFlow: training/inference workflows, dataset pipelines, model evaluation
  • NLP: classical + transformer-based pipelines (tokenization, inference, evaluation mindset)
  • Prophet: time-series forecasting, backtesting-minded evaluation
  • Experiment tracking basics, reproducible runs, model packaging for inference
• Code Quality & Testing
  • Clean code, modular design, refactoring, SOLID principles
  • Unit/integration testing, test isolation, mocking, contract testing mindset
  • Code reviews, maintaining consistent style and documentation
• Reliability & Performance
  • Latency/throughput optimization, profiling, DB query optimization
  • Production incident triage, root-cause analysis, stability improvements
• DevOps / Tooling
  • Docker (containerization, local reproducible environments)

Education

HSE University (Moscow, Russia) — BSc in Computer Science

Languages

• Russian — Native
• English — B2

Additional

• Strong interest in complex problem solving and continuous learning
• Personal interests: languages, self-education, technology exploration

Profiles

• GitHub: https://github.com/sweetd0vee
• Kaggle: https://www.kaggle.com/sweetd0ve
• LeetCode: https://leetcode.com/u/sweetd0ve
• LinkedIn: https://www.linkedin.com/in/sweetd0ve/