Data Engineer

As Data Engineer at Xebia, you will partner with engineering, product, and data teams to design and deliver scalable, high-performance data solutions. You will build and optimize data platforms and pipelines, implement cloud-native architectures, and mentor junior engineers while promoting engineering excellence across teams.

Responsibilities

• Deliver scalable and robust data systems for clients worldwide.
• Engineer data platforms with a strong focus on performance, security, and reliability.
• Design and develop data processing pipelines (batch and streaming).
• Integrate heterogeneous data sources and optimize processing workflows.
• Collaborate with Platform & Reliability engineers to build production-grade infrastructure.
• Work closely with analysts to enhance data accessibility and insights.
• Onboard and mentor new engineers within client and internal teams.

• 6+ years of experience in a senior data engineering or backend data role.
• Strong proficiency in Python with hands-on experience building data processing pipelines.
• Expertise with GCP services, especially GCS, Cloud Run ,GKE, BigQuery and Dataflow.
• Advanced SQL skills and solid understanding of relational and NoSQL databases.
• Experience with data orchestration/workflow tools (Nextflow, Airflow, etc.).
• Strong experience building cloud-native data solutions, particularly on GCP.
• Proficiency in Docker and experience deploying workloads on Kubernetes.
• Experience with version control (Git) and collaborative engineering workflows.
• Excellent English communication (written and spoken).
• Ability to work effectively within distributed teams and drive technical alignment.

Nice to have

• Knowledge of Terraform for IaC.
• Experience with PowerBI or similar BI tools.
• Understanding of ML operationalization (e.g., running models in Docker/Kubernetes).
• Basic exposure to Langfuse for observability in LLM-related pipelines.