Mid-Backend Developer Big Data Hybrid from Warsaw

• Bachelor’s degree in Computer Science or related field.
• 3+ years of experience in software/data engineering, preferably in financial services.
• Hands-on experience with Apache Spark (Scala).
• Strong background in ETL/ELT pipeline development.
• Knowledge of integration solutions (APIs, microservices).
• Familiarity with Big Data technologies and SQL databases.
• Experience with CI/CD tools (Git, GitHub, Jenkins).
• Professional English (B2+).

Preferred Qualifications:

• Experience with Python, Bash scripting, or Airflow/Control-M.
• Familiarity with Cloud platforms (Azure, AWS, Databricks, S3, Kubernetes, Docker, EMR).
• Understanding basics of cybersecurity/quality assurance (Sonar).
• Knowledge of software development lifecycle tools (HP ALM).
• Strong analytical and problem-solving skills.

This role focuses on building scalable, efficient, and robust solutions for global regulatory reporting, contributing to risk reduction and operational excellence across the Group.

This job is Hybrid - 1 day in the office (Warsaw) every 1-2 months.

,[Design and implement scalable, high-performance reporting solutions., Build Spark-based applications (Scala preferred)., Develop and maintain end-to-end ETL/ELT pipelines, including data transfer, validation, and business logic., Collaborate closely with Product Owners, Architects, Analysts, and cross-functional teams across geographies., Work in an Agile/Scrum environment with a strong focus on continuous delivery and quick feedback loops., Contribute to CI/CD pipelines and ensure high-quality delivery through unit testing, automation, and peer reviews., Document solutions in standard tools (JIRA, Confluence, ALM)., Integrate data from multiple sources, supporting a microservices-based architecture.] Requirements: Scala, ETL, Agile, Scrum, CI/CD Pipelines, Unit testing, Jira, Confluence, ALM, Degree, Data engineering, Microservices, Big Data, SQL, CI/CD, Git, GitHub, Spark, Apache Spark, Jenkins, Python, Bash script, Airflow, Control-M, Cloud platform, Azure, AWS, Databricks, AWS S3, Kubernetes, Docker, Amazon EMR, Cybersecurity, Quality assurance