Level of Experience: Mid-Senior / Senior level with strong commercial experience as a Python Developer / Python Engineer.
Python: Strong hands-on experience with Python in production environments.
Database: Very good knowledge of SQL and PostgreSQL, including experience with complex queries and large databases.
Data Processing: Strong practical experience with Pandas, PySpark, and/or Apache Spark when working with large datasets.
Large-Scale Data: Proven experience working with high-volume data and complex data structures.
Performance: Practical experience optimizing data processing, application performance, and database queries.
Data Migration: Experience with data migration, transformation, or large-scale data movement.
Education: University degree in Computer Science, Software Engineering, or another relevant technical field.
Languages: Very good English required for daily communication within an international environment.
Nice to Have
Knowledge of FastAPI, Flask, or Django.
Experience with Docker and Kubernetes.
Familiarity with Apache Kafka or other messaging technologies.
Knowledge of Apache Airflow or similar workflow orchestration tools.
Exposure to AWS, Azure, or GCP.
Experience with CI/CD pipelines.
Previous experience in financial services, asset management, or investment fund environments, particularly ETFs.
Python Engineer
About the Role
We are looking for an experienced Python Engineer to join a large-scale, technically demanding project within the financial technology sector. The role will involve developing and maintaining backend and data-intensive solutions using Python and PostgreSQL, working with complex systems, large datasets, and performance-critical applications.
You will work within an international engineering environment and contribute to the development, optimization, and maintenance of scalable software solutions.
Key Responsibilities
Develop and maintain backend applications and services using Python.
Design, implement, and optimize solutions based on PostgreSQL.
Work with large datasets and complex database structures.
Develop and maintain data processing and transformation components.
Optimize application performance, database queries, and data processing workflows.
Support system integrations and data migration initiatives.
Troubleshoot, debug, and resolve technical issues across backend environments.
Collaborate with international engineering teams on technical requirements and solution design.
Maintain, refactor, and enhance existing applications and services.
Working Model & Logistics
Location: Warsaw, Poland – hybrid model
Start Date: ASAP.
,[] Requirements: Python, PostgreSQL, System integration, SQL, pandas, PySpark, Spark, Data structures, Data migration, FastAPI, Flask, Django, Docker, Kubernetes, Apache Airflow, CI/CD Pipelines, Logistics
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