Python Data Engineer @ Link Group
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.
Candidate Profile
- 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