Data Engineer
Pubblicato il 19-10-2026 - GCS Recruitment Specialists in Italia
Data Engineer (Python / Distributed Data Platforms)
Relocation to Malta Required | Permanent | Remote from Malta
We have partnered with a growing European technology company that is investing heavily in its data platform and engineering capabilities.
As part of their expansion, they are seeking Data Engineers across multiple levels, including:
- Data Engineer II (3-5 years)
- Data Engineer III (5-8 years)
- Staff Data Engineer (10-12 years)
This is an opportunity to build and scale modern distributed data platforms capable of handling large-scale data workloads while working with a cutting-edge open-source technology stack.
What You’ll Be Doing
- Design and develop scalable batch and real-time data pipelines
- Build reliable distributed data systems handling large-scale datasets
- Work with diverse data sources, APIs, legacy systems, and modern applications
- Own data products and pipelines throughout their lifecycle
- Improve platform reliability, observability, and performance
- Contribute to architecture and technical design decisions
- Support production environments and drive operational excellence
Technology Stack
- Python
- PySpark & Pandas
- SQL & PostgreSQL
- Apache Spark
- Kafka / Redpanda
- Airflow / Temporal
- Apache Iceberg / Hudi
- S3-Compatible Object Storage
- Kubernetes
- GitOps
- Prometheus & Grafana
- Go (or willingness to learn)
What We're Looking For
- Strong experience in Data Engineering, aligned to the level applied for
- Solid Python and SQL expertise
- Experience building and maintaining production-grade data pipelines
- Hands-on experience with distributed data processing technologies
- Understanding of batch and streaming architectures
- Experience with orchestration frameworks such as Airflow, Temporal, or similar
- Familiarity with cloud-native environments and Kubernetes
- Strong software engineering and problem-solving skills
Why Join?
- Competitive salary and benefits package
- Relocation support to Malta
- Work on large-scale di