Python Data Engineer

• 3–5 years of professional experience in data engineering or a closely related software engineering role.
• Strong data warehousing knowledge: dimensional modeling, normalization vs. denormalization, ETL/ELT design, SCDs, and warehouse performance considerations.
• Hands-on experience with Apache Spark using PySpark, including building and optimizing distributed data processing jobs.
• Strong general Python development skills with a solid programming and computer-science foundation (data structures, algorithms, OOP, testing).
• Proficiency in SQL, including complex queries, window functions, and query optimization.
• Experience version control (GitLab).
• Understanding of data quality, reliability, and pipeline monitoring practices.

Nice to have:

• Experience with cloud data platforms (AWS, Azure, or GCP) and their data services.
• Familiarity with modern data platforms or lakehouse technologies
• Experience with CI/CD for data pipelines and infrastructure-as-code.
• Exposure to streaming data processing (e.g., Spark Structured Streaming, Kafka).
• Experience working in Agile teams.

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.

About the Role

We are looking for a Senior Data Engineer with strong data warehousing fundamentals and hands-on Spark (PySpark) experience to design, build, and maintain scalable data pipelines. You will work closely with analysts, data scientists, and product teams to turn raw data into reliable, well-modeled datasets that power reporting, analytics, and downstream applications. This role suits a strong general-purpose Python developer with a solid programming background who enjoys building robust, production-grade data systems.

What We Offer

• Real impact on the development of the company and the product.
• Work in an experienced team that actively shares knowledge.
• A clear growth path supported by regular feedback and transparent career development.
• Training budget for courses and conferences of your choice.
• An additional day off on your birthday.
• An additional day off for parents.
• Equipment tailored to your needs.
• Private medical care and group insurance.
• Access to an e-learning platform for learning English and a benefits platform.
• Access to a wellbeing platform, including workshops and private therapy sessions.
• Remote work, work from our Warsaw office, or from a coworking space in your city.
• Regular team integration events.

,[Design, build, and maintain batch and incremental data pipelines using Spark (PySpark) on large datasets., Model and develop data warehouse layers (staging, dimensional, and serving) using sound DWH principles such as star/snowflake schemas, fact and dimension tables, and slowly changing dimensions (SCDs)., Develop and optimize ETL/ELT workflows, ensuring data quality, accuracy, and timeliness., Write clean, well-tested, and maintainable Python code, applying solid software engineering practices (version control, code review, modular design)., Tune Spark jobs for performance and cost - partitioning, caching, join strategies, and resource configuration., Build and maintain orchestration workflows and monitor pipeline health., Collaborate with stakeholders to translate business and analytics requirements into reliable data models., Contribute to data architecture decisions, documentation, and engineering standards within the team., Mentor junior engineers through code reviews and knowledge sharing.] Requirements: Python, ETL, ELT, SCD, Apache Spark, PySpark, SQL, GitLab, AWS, Azure, GCP, CI/CD, Kafka Tools: . Additionally: Sport subscription, Training budget, Private healthcare, An extra day off on your birthday, An extra day off for parents.