Wally Hormi

Context: Production migration and optimization of the data infrastructure towards a modern, cloud-native, and scalable platform.

Key achievements:

• Core Engine & Architecture Migration: Complete migration of legacy R programs to PySpark on a native Databricks environment, with the implementation of a Medallion architecture (Bronze to Gold layers).

• Batch Industrialization & Automation: Design, development, and production deployment of complex Databricks Workflows to automate batch ingestion (Trigger mode), ensuring daily data delivery before the start of the business day.

• Handling Complex Volumes: Processing and optimization of data pipelines handling several million rows and hundreds of columns to feed critical company Datamarts.

• Data & BI Reporting: Creation and maintenance of secure and efficient connections between the Databricks environment and Power BI dashboards to enable Data Analysts to generate business insights.

• DevOps & Git Practices: Management of the Git environment for script versioning, technical collaboration, and deployment security under Azure DevOps.

Technical environment: Databricks, PySpark, Python, Spark SQL, Azure DevOps, Git, R.

Context: Strategic mission to take over technical operations and ensure business continuity. Took lead autonomously on a critical data scope following the sudden departure of the previous team. Stabilized the existing architecture and provided technical leadership for a major Proof of Concept (POC) between DataGalaxy and Franprix.

Key achievements:

• Ownership & Autonomy: Ultra-fast skill acquisition on a complex, undocumented architecture. Comprehensive audit, security, and operational maintenance of the overall infrastructure.

• Pipelines & Automation: Design and implementation of robust Python scripts connected to Snowflake to generate functional reports and automate the daily email delivery of results to collaborators.

• Governance & Cataloging: Complete documentation of existing Python code and cataloging of tables, key performance indicators (KPIs), and MicroStrategy cubes to structure the POC.

Technical environment: Snowflake, Python, SQL, Docker, GitLab CI/CD, DataGalaxy, MicroStrategy.

Context: Strategic international migration of 1,400 markets (one of the largest global migrations at the time) for GDPR compliance of digital tracking frameworks to GA4 and GTM.

Key achievements:

• Automation & OOP Programming: Design and development of complex Python scripts in Object-Oriented Programming (OOP) combined with Selenium to programmatically recreate and migrate GA4 properties via dedicated Google APIs.

• GTM Container Migration & Update: Automation of mass migration, creation, and updates of digital data containers on the GTM tool for all international properties and accounts (from JSON configuration files).

• Cross-Platform Ingestion & Orchestration: Interconnection with Adobe Analytics (via R) and design of Dataiku flows/scenarios to feed and structure target databases (BigQuery) on Google Cloud Platform (GCP).

Technical environment: Python, Google Cloud Platform (GCP), BigQuery, Dataiku, Selenium, R, Git.