Freelancer profile translated to English.
Back to original languageAbout Boussaad
Data Engineer with 5 years of experience in designing and optimizing modern data architectures (Snowflake, DBT, GCP, AWS). Expertise in developing efficient and automated ETL/ELT pipelines, ensuring data reliability and quality. I have supported major players in luxury and insurance in their data transformation projects, implementing scalable cloud solutions to accelerate business decision-making.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 15km)
Experience
- AVISIA,Data EngineerSOCIAL NETWORKSMay 2025 - November 2025 (6 months)Paris, FranceOn behalf of the Marketing department of AVISIA, participation as a Data Engineer in the automation of social media data retrieval for business analysis.● Gathering requirements from the Chief Marketing Officer to define objectives and key indicators.● Data collection: Automated extraction of Avisia's social media data via Fivetran, with centralized storage in BigQuery.● Creation of a scraping script to enrich data not directly accessible via API.● Containerization of code with Docker, then deployment of the image in GCP Artifact Registry.● Implementation of a Cloud Run Job to execute the image, orchestrated by Cloud Scheduler to automate launches.● Creation of a transformation pipeline with Dataform to structure, clean, and model the data.● Automation of table updates via the Dataform scheduler to ensure daily data freshness.Environment and tools: Google Cloud Platform (GCP), Fivetran, BigQuery, SQL, Dataform, Google Cloud Shell, Python, Docker, Google Cloud Artifact, Google Cloud Run, Google Cloud Scheduler
- MUTEX,Data EngineerBANKING AND INSURANCEJanuary 2025 - May 2025 (4 months)Paris, FranceDesign and implementation of controls to identify anomalies and monitor data quality in the people registry. Development of a synthetic report to detect inconsistencies, track key indicators, and provide a reliable basis for corrective action plans.● User needs analysis: Gathering and formalizing business requirements to define data quality criteria and controls.● Data extraction and transformation: Extraction of data from the AWS S3 data lake, followed by modeling and transformation in Python to obtain structured datasets.● Development of a data control pipeline: Design and implementation of a pipeline under AWS SageMaker integrating advanced anomaly detection and reporting mechanisms.● Performance optimization: Improving the efficiency and speed of processing pipelines and quality controls on AWS SageMaker for more efficient analysis.● Creation of an interactive report: Development of a Power BI report for monitoring anomalies and tracking data quality over time.● Technical and functional documentation: Detailed writing of documentation to ensure traceability and knowledge transfer on the developed solutions.Environment and tools: Agile Methodologies, Python, AWS, Amazon S3, Amazon SageMaker, Power BI.
- diptyqueData EngineerLUXURY GOODSJanuary 2022 - December 2024 (2 years and 11 months)Paris, FranceOn behalf of the Data and BI department, within a luxury perfume house, acting as a Data Engineer.● User needs analysis and formalization: Gathering, analyzing, and documenting business requirements to guide data architecture evolution.● Data Modeling Design: Development of optimized modeling schemas to efficiently structure analytical data.● Creation and optimization of data ingestion and transformation workflows, ensuring smooth integration between various sources and Snowflake.● Automation of data ingestion: Configuration and management of Fivetran connectors to automate data import into Snowflake.● Data transformation with DBT: Implementation of structured pipelines (staging, intermediate, and marts) to provide analysis-ready tables, ensuring data quality.● Implementation of quality controls: Deployment of verification mechanisms to ensure the integrity, consistency, and reliability of processed data.● Version control and CI/CD management: Administration of DBT script versioning and automated deployment via CI/CD pipelines on GitLab, ensuring code robustness.● Performing systematic checks and code reviews to maintain the quality and maintainability of developed solutions.● Writing and updating documentation on Confluence to promote traceability and knowledge sharing.● Monitoring and maintenance of the analytical architecture.● FinOps Optimization: monitoring and adjusting dbt pipelines to control costs and improve performance.● Supporting data teams: providing support and promoting best dbt practices to facilitate data adoption within the company.Environment and tools: Agile methodology, Fivetran, Snowflake, Postman, SQL, Python, DBT Cloud, Gitlab, Git, Tableau, JIRA, Confluence
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Education
- Master 2 Information Technology and Data Science in BusinessUniversité Paris IMaster 2 Techniques d'Information et Data-science en Entreprise
- AWS Certified Solutions Architect – Associate Certificationà AWS Certified Solutions Architect – Associate Certification