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Othmane WafiOW

Othmane Wafi

Senior Data Engineer

€555/day
Paris, FR
3-7 years
Spark
Databricks
Python
SQL
Microsoft Azure

Average response time: 1 hour

Freelancer profile translated to English.
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About Othmane

Graduated engineer from EMSI Casablanca and Master 2 MIAGE from the University of Rennes 1, I have always been passionate about IT, new technologies, and their impact on business transformation.

Throughout my career, I have had the opportunity to collaborate with various companies on concrete and diverse projects, ranging from software and web development to Big Data and Cloud initiatives. These experiences have allowed me to develop solid technical expertise while working in agile and results-oriented environments.

🚀 Today, I am particularly drawn to the Big Data and Cloud Computing domain, where I have already acquired practical skills in data pipelines, orchestration, and cloud solution industrialization. I wish to contribute to ambitious projects in this field and continue to strengthen my expertise in large-scale environments.

Adaptability and autonomy in various contexts.

Significant experience in web and software development.

Regular practice of agile methodologies.

Motivated, curious, and ambitious spirit, always ready to take on new challenges.

My goal: to use my passion for technology and my software and data engineering skills to serve innovative and high-impact projects.

Open to new opportunities in the Big Data, Cloud, and Data Engineering fields.

  • French

    Native or bilingual

  • English

    Fluent

  • Spanish

    Fluent

Can work on-site
Paris (up to 50km)

Experience

  • EDF
    Data Engineer and Manager
    November 2025 - Today (9 months)
    • - Gathering business needs through workshops and stakeholder discussions
    • - Writing detailed technical and functional specifications
    • - Data modeling (star and snowflake schemas) for optimizing analytical uses
    • - Defining and implementing data lakehouse architectures (Bronze / Silver / Gold)
    • - Designing Gold data models adapted to BI and reporting needs
    • - Participating in architecture and data technology choices based on use cases
    • - Implementing best practices for data management: historization, versioning, S3 storage, backup strategy
    Developing and maintaining data pipelines:
    • - Ingestion to S3
    • - Transformation via Python / Spark / SQL
    • - Workflow orchestration with Airflow
    • - Data exploitation and processing via Spark, Trino, and Jupyter notebooks
    • - Integration of data from heterogeneous systems (PostgreSQL, Oracle, APIs)
    IoT & API Data
    • - Defining and implementing IoT data recovery plans
    • - Integration of data from EDF sensors via API (Cumulocity)
    • - Managing large-volume and real-time data streams
    Data Visualization & Reporting
    • - Creating reports and dashboards with Power BI
    • - Structuring data for BI exploitation (PostgreSQL / Oracle)
    • - Translating business rules into technical logic (and vice versa)
    Tech: GIT, AIRFLOW, SPARK, PYTHON, SQL, ORACLE, POSTREG, TRINO, ICEBERG
  • NATIXIS
    Data Engineer
    May 2023 - October 2025 (2 years and 5 months)
    Project: LCLF Team – Fraud Detection (European context, SAFE Agile)
    • Active participation in several projects within an agile team (SAFe) in an international context (English communications).
    • Cross-border payments project for the European Commission in preparation for the 2024 Olympics:
    • Implementation of a new end-to-end pipeline on BigQuery to aggregate data from various existing GCP tables within the BPCE group. - Transformation and quality control of data (SQL, Python).
    • Generation of normalized XML and CSV files for transmission to authorities.
    • Orchestration and monitoring of pipelines with Airflow (automatic reprocessing in case of failure).
    • Data security & governance: implementation of automated GCP permission management with Terraform, management of roles and sensitive access.
    • Optimization of ingestion pipelines: reduction of processing times by 30% through BigQuery partitioning, clustering, and SQL refactoring.
    • Implementation of operational reporting: exposure of data on Power BI to enable business teams to analyze fraud indicators.
    • Continuous improvement: contribution to the standardization of Terraform templates, improvement of CI/CD best practices (GitLab/Jenkins).
    • Support and maintenance: monitoring of production projects, bug fixing, and integration of new data sources.
    • Transverse context: regular interaction with other data teams within the group (Finance, Risk, Compliance) to align pipelines and avoid duplication.
    Tech: GCP (BigQuery, Pub/Sub, Dataproc, Airflow), Jenkins, Python, SQL, Terraform, Git, Power BI
    Methodology: Agile SAFE (PI Planning, daily stand-up, sprint reviews)
  • L'OREAL
    Data Engineer
    June 2022 - May 2023 (11 months)
    Active participation in several projects within an agile team in an international context (coordination with EMEA and Global teams) Luxury:
    • - Design and implementation of automated ELT pipelines with dbt, feeding BigQuery from the L'Oréal Data Lake (Global and EMEA zones).
    ◦ - Data modeling (tables, views, datasets) in BigQuery with optimization via partitioning and clustering.
    ◦ - Optimization of processing performance and reduction of loading times.
    ◦ - Implementation of technical and business documentation via dbt (docs + lineage).
    ◦ - Construction of analytical models for market share comparison (L'Oréal vs Amazon, Sephora…).
    ◦ - Automation of transformations via dbt, reducing analysis time from several days to a few hours.
    ◦ - Optimization of SQL queries and BigQuery costs.
    ◦ - Implementation of data quality tests (dbt tests) and monitoring of pipeline reliability.
    ◦ - Implementation and improvement of ingestion pipelines (batch) with transformation via dbt and storage on BigQuery.
    • - Optimization of robustness, error management, and cost reduction on GCP.
    • - Design and realization of ELT pipelines on BigQuery, integrating advanced transformations: partitioning, clustering, materialized views, incremental tables (dbt incremental models).
    • - Industrialization of pipelines: CI/CD, deployment, monitoring, incident management, and continuous improvement.
    Tech DBT, GCP (BigQuery, Build), Python, SQL, Terraform, Git, Power BI
Check out Othmane's experience

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Education

  • Master
    2019
    Master
  • Engineering degree in Computer Science and Networks
    Moroccan School of Engineers (EMSI)
    2023
    Diplôme ingénieur en informatique et réseaux

Skill set

Cloud GCP
Airflow

Categories