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