Data Engineer
AI Summary
Designs, builds, and maintains scalable data pipelines and integration mechanisms for a centralized data platform, ensuring data quality, reliability, and consistency across the company.
About this role
XTB is a global company from the financial industry, focusing on online trading of financial instruments. We are the largest FinTech in Poland and a leader in Central and Eastern Europe, and the range of our operations covers several countries, including Asia and South America. At XTB, we focus on the development of our employees, giving them opportunities to gain knowledge and skills in various fields, as well as offering a number of training and development programs. If you are looking for challenges and want to gain valuable experience in an international business environment, XTB is the right place for you.
We are a certified Great Place to Work company.
We are looking for a Data Engineer to join the Core Data Platform team to co-create and develop a centralized data platform used by teams across the company. In this role, you will be responsible for building scalable data integration mechanisms from various source systems, developing shared platform components and standards, and ensuring high data quality, reliability, and consistency.
Responsibilities
Designing, building, and maintaining scalable data processing pipelines using SQL, Python, and Apache Spark / PySpark.
Working with raw data and designing methods for its integration into the data platform.
Developing CI/CD pipelines for data engineering solutions.
Creating and maintaining Infrastructure as Code solutions.
Integrating the data platform with other systems and applications.
Participating in architectural decision-making and defining engineering standards.
Conducting code reviews, documenting solutions, and sharing knowledge with team members.
Requirements
At least 3 years of experience as a Data Engineer or in a related software engineering role.
Proficiency in Python and the ability to write clean, testable production code.
Hands-on experience with Apache Spark.
Advanced SQL skills (query optimization on large datasets).
Strong understanding of data warehouse design principles and data modeling.
Practical knowledge of ETL/ELT processes.
Familiarity with data quality, monitoring, and pipeline reliability.
Experience working with relational databases, including an understanding of how they work, data modeling, and optimization.
Understanding of REST and gRPC standards for system integration.
Experience with workflow orchestration tools (e.g., Airflow, Dagster, or similar).
Knowledge of CI/CD pipeline building and maintenance principles.
Strong analytical problem-solving skills and attention to detail.
Effective communication skills and the ability to collaborate in a team.
Openness to learning and exploring new technologies and methodologies.
Nice to have
Experience with dbt.
Experience with Kafka, Pub/Sub, or other event streaming systems.
Experience building near-real-time / real-time pipelines.
Experience working with Infrastructure-as-Code tools.
Understanding of CDC (Change Data Capture) and data integration from transactional systems.
Experience with Databricks or other lakehouse platforms.
What we offer
Benefits
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