Data Engineer
Domain: Banking & Finance
Experience: 5+ years
Employment Type: Full-time
Location: Hybrid — Kraków, Poland
Project Duration: November 2, 2026 – April 30, 2027
About the Project
We are looking for Data Engineer to join a modern engineering environment and work on reliable, scalable data solutions.
The role focuses on building data pipelines and processing frameworks, integrating multiple platforms and systems, and making data accessible, governed, and fit for purpose. The team works with Scala, Java, Python, Apache Airflow, and cloud technologies.
Experience with data fabrics, cloud platforms, and Apache Airflow will be particularly valuable.
Responsibilities
- Design, develop, and maintain robust data pipelines and engineering frameworks
- Build scalable data processing solutions using Scala, Java, and Python
- Integrate data platforms, applications, APIs, and other technology components
- Develop and support workflows using Apache Airflow
- Work with cloud-based data services and infrastructure
- Contribute to data fabric architectures, including data integration, discovery, access, and governance
- Develop and consume APIs to support data movement and system interoperability
- Apply software engineering best practices, including version control, testing, code reviews, documentation, and CI/CD
- Monitor, troubleshoot, and improve the performance, resilience, and quality of data solutions
- Collaborate with data architects, software engineers, platform teams, analysts, and business stakeholders
- Support security, data protection, and operational controls throughout the engineering lifecycle
Requirements
- Professional experience in data engineering, software engineering, or a closely related field
- Strong programming skills in Scala, Java, and Python
- Strong knowledge of SQL / DML
- Experience designing and implementing data pipelines, processing frameworks, or integration services
- Experience integrating multiple tools, platforms, and systems
- Hands-on experience with Apache Airflow, including DAG development, scheduling, monitoring, and troubleshooting
- Understanding of REST APIs, authentication, and error handling
- Experience working with cloud platforms and cloud-native engineering practices
- Familiarity with data architecture, data integration patterns, and data quality
- Experience with Git, automated testing, and CI/CD
- Ability to investigate complex technical issues and communicate solutions clearly
- Degree, equivalent qualification, or demonstrable professional experience in computer science, engineering, data, mathematics, or a related field
Nice to Have
- Experience with Google Cloud Platform (GCP), including BigQuery, Cloud Storage, Pub/Sub, Dataflow, or Dataproc
- Experience with data fabric architectures, metadata, data catalogues, lineage, or federated data access
- Familiarity with Apache Spark and other distributed processing technologies
- Experience with containers, orchestration, or Infrastructure as Code
- Knowledge of security, access control, encryption, and regulatory requirements in data environments
- Experience working in Agile, product-oriented, or DevOps environments
- Relevant cloud, data engineering, or software engineering certifications
Soft Skills
- Strong ownership and accountability for deliverables
- Ability to collaborate effectively across engineering, architecture, operations, and business teams
- Ability to balance delivery speed with maintainability, resilience, and control
- Structured approach to problem-solving and continuous improvement
- Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
- Collaborative mindset and appreciation of diverse perspectives
Tech Stack
Scala, Python, Java, SQL, Apache Airflow, Apache Spark, REST APIs, Git, CI/CD, GCP, Data Integration, Data Fabric