

We are looking for a Senior Data Engineer with strong expertise in GCP, Databricks, and Airflow to design and implement a GCP Cloud Native Data Processing Framework. The ideal candidate will work on building scalable data pipelines and help migrate existing workloads to a modern framework.
- Shift: 2 PM 11 PM
- Work Mode: Hybrid (3 days a week) across Xebia locations
- Notice Period: Immediate joiners or those with a notice period of up to 30 days
Key Responsibilities:
- Design and implement a GCP Native Data Processing Framework leveraging Spark and GCP Cloud Services.
- Develop and maintain data pipelines using Databricks and Airflow for transforming Raw → Silver → Gold data layers.
- Ensure data integrity, consistency, and availability across all systems.
- Collaborate with data engineers, analysts, and stakeholders to optimize performance.
- Document standards and best practices for data engineering workflows.
Required Experience:
- 7-8 years of experience in data engineering, architecture, and pipeline development.
- Strong knowledge of GCP, Databricks, PySpark, and BigQuery.
- Experience with Orchestration tools like Airflow, Dagster, or GCP equivalents.
- Understanding of Data Lake table formats (Delta, Iceberg, etc.).
- Proficiency in Python for scripting and automation.
- Strong problem-solving skills and collaborative mindset.
⚠️ Please apply only if you have not applied recently or are not currently in the interview process for any open roles at Xebia.
Looking forward to your response!
Best regards,
Vijay S
Assistant Manager - TAG

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