Python - Data Engineer

Education - Master's degree in Computer Science, Software Engineering, or a related field (or
equivalent practical experience).
- Experience - 5+ years building production Python backends for data-intensive applications.
- Python Mastery - Modern Python (3.10 +) with asyncio, typing, dependency injection, and
packaging best practices.
- ETL Skills - Experience designing batch or streaming pipelines; comfort with Kafka, RabbitMQ, or
similar tools.
- Database Skills - Strong Postgres knowledge: migrations (Alembic, Django ORM), query tuning,
partitioning, backup/restore.
- Async Orchestration - Hands-on with async tools like Airflow, Dagster, or Celery for scheduling
and monitoring jobs.
- API Engineering - Proven ability to implement secure, versioned REST/GraphQL APIs with auth,
rate-limiting, and RBAC.
- Testing & DevOps - Familiarity with Pytest, Docker, Kubernetes, Terraform, and GitHub Actions
(or similar).
- Soft Skills - Clear written and verbal communication; collaborative mindset.
Nice-to-Haves
- Time-series or columnar DBs (TimescaleDB, ClickHouse, InfluxDB).
- Knowledge of financial market-data protocols (FIX, FAST) or regulatory feeds.