Graba Fares

Data Engineer specialized in Azure Databricks, Spark, and Lakehouse architectures.

I help companies modernize their information systems by assisting them in migrating to more performant data platforms and tools (Databricks, Cloud, distributed architectures). My expertise covers the entire ETL lifecycle — design, development, industrialization — with a particular focus on the reliability and performance of pipelines.

I work on migration, modernization, and industrialization of Data Platforms: data ingestion, PySpark/SQL pipelines, Medallion architecture, DataOps, CI/CD, governance, data quality, security, and cloud cost optimization.

My main topics:

• Azure Databricks Lakehouse Architecture

• Development and industrialization of Data Engineering pipelines

• Spark / PySpark optimization on large volumes

• Implementation of DataOps and CI/CD practices

• Governance, Data Quality, GDPR, and access security

I have supported large accounts in finance, retail, aeronautics, lottery, and logistics, with challenges related to production, performance, reliability, compliance, and scalability.

My goal: to help teams transition from a complex or artisanal data platform to a reliable, industrialized, governed, and business-value-oriented platform.

Main expertise: Azure Databricks, Data Engineering, Apache Spark, PySpark, Delta Lake, Lakehouse, Azure Data Factory, GCP/Big Query, CI/CD, Data Governance, Data Quality, SQL, Python, Scala, Airflow.