Freelancer profile translated to English.
Back to original languageAbout Omar
Tech Lead Data / Data Engineer specializing in Azure Databricks, Spark, and Lakehouse architectures.
I help companies design, industrialize, and optimize modern data platforms on Azure Databricks, Azure Data Lake, Azure Data Factory, Delta Lake, and Apache Spark.
I work on data platform migration, modernization, and industrialization projects: data ingestion, PySpark/SQL pipelines, Medallion architecture, DataOps, CI/CD, governance, data quality, security, and cloud cost optimization.
My main areas of focus:
• 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
• Tech Lead support for Data Engineer, BI, and Data Science teams
I have supported large enterprise environments in insurance, finance, retail, and energy sectors, with challenges related to production, performance, reliability, compliance, and scalability.
My goal: to help teams transition from complex or artisanal data platforms to reliable, industrialized, governed, and business-value-oriented platforms.
Core Expertise: Azure Databricks, Data Engineering, Apache Spark, PySpark, Delta Lake, Lakehouse, Azure Data Factory, DataOps, CI/CD, Data Governance, Data Quality, FinOps, Power BI, SQL, Python.
French
Native or bilingual
English
Native or bilingual
Can work on-site
Paris (up to 50km), Lyon (up to 50km), Toulouse (up to 50km), Montpellier (up to 50km), Lille (up to 50km)
Experience
- ENGIETech Lead DataENERGY AND UTILITIESJanuary 2026 - Today (7 months)Colombes, France
- Migration of a Palantir Foundry data platform to a Lakehouse architecture based on AWS and Databricks, enabling the modernization and opening of the Data Platform.
- Design and implementation of a scalable data architecture based on Data Lake and Delta Lake to centralize data sources and improve dataset governance.
- Development and industrialization of PySpark transformation pipelines on Databricks for large-scale data ingestion, transformation, and provisioning.
- Structuring data according to the Medallion architecture (Bronze, Silver, Gold) to improve the quality, performance, and reliability of analytical processing.
- Optimization of Spark and Databricks cluster processing performance to ensure scalability and reliability of production pipelines.
- Implementation of DataOps practices including deployment automation, pipeline monitoring, and continuous improvement of data flow reliability.
- Optimization of cloud platform operating costs (FinOps) and improvement of the efficiency of Big Data processing resources used.
- Groupe AFFLELOUTech Lead DataRETAIL (SMALL BUSINESS)January 2024 - January 2026 (2 years)Puteaux, France
- Piloting security and compliance: monitoring cloud infrastructure with a high level of requirement for confidentiality, regulatory compliance, and resilience.
- Vision and deployment of cloud services: defining and implementing solutions adapted to business needs, ensuring performance and scalability.
- Data architecture and governance: designing robust and scalable pipelines, integrating FinOps practices, advanced observability, and alignment with governance standards (GDPR, audits, data stewardship).
- Technical and methodological leadership: promoting good development practices (Git flow, code review), mentoring Data Science, Data Stewards, and Data Analysts teams, and leading strategic workshops with stakeholders.
- Influence and technological partnership: close collaboration with business units and continuous engagement with vendors (Azure, Databricks, Informatica…), ensuring proactive adoption of innovations and the relevance of deployed solutions.
- iQeraSenior Data EngineerBANKING AND INSURANCEJuly 2023 - January 2024 (6 months)Paris, France
- Piloting the migration and integration of heterogeneous data sources (IBM, Postgres…) to Azure Data Lake, with optimized transformation and storage in Delta and Parquet formats.
- Development of AZCopy scripts to automate secure data transfer from internal servers to the Data Lake.
- Mastery of Python, SQL, and the PySpark 3 framework for ingestion, transformation, and industrialization of data flows.
- Advanced use of Azure Databricks, Data Factory, DevOps, and Storage Gen2 services to orchestrate and supervise pipelines.
- Design of multi-zone ingestion and processing pipelines (bronze, silver, gold), with ACL management and artifact deployment via Azure DevOps, ensuring reliability, scalability, and compliance of data environments.
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Education
- TPM1x: Creative Problem Solving and Decision Making Neural Networks and Deep Learning Academy Accreditation - Azure Databricks Platform Architect Microsoft Certified: Azure Data Fundamentals Databricks Certified Associate Developer for Apache Spark 3.0TPM1x: Creative Problem Solving and Decision Making Neural Networks and Deep Learning Academy Accreditation - Azure Databricks Platform Architect Microsoft Certified: Azure Data Fundamentals Databricks Certified Associate Developer for Apache Spark 3.0
- Engineering Degree, Information Systems Engineering (ISI)Grenoble INP - Ensimag2020Diplôme d'ingénieur, Ingénierie des Systèmes d'Information (ISI)