Data Platform Engineer
On-siteFull-time
Prishtina
We at XToka are looking for a Data Platform Engineer, a mid-level specialist who will support the adoption, optimization, and best-practice use of our modern data platform.
You will help our teams work smarter with data by building scalable pipelines, improving platform operations, documenting standards, and assisting engineers/analysts in getting the most out of technologies like Spark, Delta Lake, and our lakehouse environment.
This role is ideal for someone with solid experience in big-data engineering who wants to grow into a platform-lead/expert position in the future.
Responsibilities
- Support the rollout and adoption of our data platform by helping define best practices, reusable assets, and internal standards.
- Build and maintain scalable data pipelines using Spark, Delta Lake, and cloud-native tools.
- Collaborate with Data Engineering, Analytics, BI, and IT to deliver reliable, high-performance data solutions.
- Assist in platform optimization (cluster tuning, cost optimization, job scheduling, orchestration improvements).
- Contribute to enablement: documentation, internal guides, workshops, and office-hours sessions for engineers and analysts.
- Evaluate new platform features (cataloguing, workflow automation, streaming, governance, etc.) and help integrate them.
- Promote data quality, governance, and automation across the data lifecycle.
Requirements
- 3+ years experience in Data Engineering, Data Platform, or Analytics Engineering
- Hands-on experience working with Spark-based data processing
- Experience with Delta Lake or similar transactional lake technologies
- Strong SQL + solid Python experience
- Understanding of cloud data platforms (Azure/AWS/GCP)
- Familiarity with ETL/ELT pipelines and distributed data workloads
- Clear communication and willingness to support/train other teams
- Experience with data cataloguing/governance frameworks (preferred)
- Understanding of workflow/orchestration tools (ADF, Airflow, Databricks Workflows, Prefect, etc.) (preferred)
- Familiarity with ML pipelines, model tracking (MLflow), or analytics environments (preferred)
- Experience with CI/CD and infrastructure-as-code concepts (preferred)
- Certifications in data engineering or cloud technologies (preferred)