Wijdane RAMMACH

– Growth Countries project - Jan 2025 – Present Designed and implemented a retail analytics platform based on transactional sales data, enabling FMCG suppliers and Carrefour teams to analyze market performance, competitive dynamics and shopper behavior. Responsibilities: Retail Data Platform & Modeling – Designed the data architecture integrating large-scale retail transactional datasets, including sales transactions, product hierarchy, store metadata and supplier information. – Built scalable ELT pipelines in BigQuery and DBT to process high-volume retail transaction data across multiple markets. – Designed analytics-ready datamarts enabling sales performance monitoring, category analysis and supplier benchmarking. – Implemented detention metrics based on sales data, enabling analysis of product distribution and sales presence across stores and markets. Analytics Enablement – Built the semantic modeling layer in Looker (LookML) enabling self-service analytics for Carrefour business teams and FMCG suppliers. – Delivered multiple Looker dashboards enabling suppliers to monitor: – sales performance – competitive benchmarking – shopper migration trends – customer segmentation insights Competitive & Shopper Analytics – Developed advanced competitive benchmarking analytics, allowing FMCG suppliers to compare their performance against competitors across categories. – Implemented shopper migration analysis, identifying customer switching behaviors between brands and competitors. – Built customer segmentation models based on transaction data to analyze purchasing patterns and shopper profiles. Supply Insight project - Feb 2023 – Dec 2024 Responsibilities: Supply Chain & Stock Analytics Platform – Designed a supply chain analytics platform enabling Carrefour teams to monitor supplier service levels, stock availability and operational supply chain performance. Supply Chain Data Platform – Designed and implemented data pipelines integrating supply chain datasets, including stock levels, deliveries, product availability and supplier logistics performance. – Built scalable ELT pipelines in BigQuery to process supply chain data and generate operational KPIs. – Designed analytics-ready datamarts supporting supply chain performance monitoring and stock analytics. Stock Analytics – Implemented stock detention metrics, enabling analysis of product presence and availability across stores. – Developed analytics models to monitor stock coverage, product availability and supply chain efficiency. Operational Analytics – Developed Looker semantic models and dashboards enabling internal Carrefour teams to monitor: – supplier service levels – stock availability – supply chain performance – operational KPIs related to deliveries and logistics Technical Leadership – Led the design and optimization of scalable data pipelines supporting multiple operational analytics use cases. – Collaborated with supply chain stakeholders and business teams to translate operational needs into scalable data solutions.

– Collaborated with report owners, data project leads, and Power BI consultants to develop shared datasets and reports for the Supply Chain and Finance domains. – Designed and architected data lake layers to optimize shared domain datasets for analytics. – Built and maintained multiple data pipelines, handling end-to-end ETL/ELT processes for data ingestion and transformation in GCP. – Created new datasets, tables, and views in BigQuery to support advanced data analytics and reporting. – Loaded data into target tables using stored procedures in GCP BigQuery. – Utilized REST APIs with Python to ingest data from external sites into BigQuery. – Created BigQuery authorized views to implement row-level security for Power BI reporting. – Monitored BigQuery and Cloud Dataflow jobs across environments using Stackdriver. – Automated data loading processes using Terraform and GitHub to streamline operations.

Supply Chain Project: – Collaborated with stakeholders to gather requirements and authored detailed functional specifications for supply chain data modules. – Designed and implemented data pipelines in PySpark and Spark SQL on both Cloudera and Databricks, ensuring scalability and reliability across environments. – Built pipelines to ingest large-scale data from ADLS, S3, and DB2, tailored for either Hive or Delta Lake as target layers, based on the platform. – Transformed and aggregated datasets using Azure Data Factory's mapping data flow and PySpark, enabling accurate referential mapping for analytics and reporting. – Integrated transformed data into Hive for Cloudera-based pipelines and Delta tables for Databricks-based pipelines, supporting advanced analytics and real-time reporting. – Streamlined data ingestion from DB2 into Snowflake using Informatica Cloud, reducing latency and enhancing data accessibility. – Developed PySpark jobs on Databricks to calculate supply chain KPIs, including Forecast Accuracy and Delivery Metrics, empowering data-driven decision-making. – Created Spark SQL views for Power BI dashboards, enabling actionable insights for monitoring supply chain operations. ISNART Project: Analyzed spend data for research and development projects. – Conducted business analysis and technical design sessions with stakeholders to define project requirements. – Defined data modeling strategies and structures to ensure effective data integration and analysis. – Ingested data from DB2 and other external sources into Hive Cloudera on AWS. – Designed and implemented ETL pipelines using Informatica BDM for data extraction, transformation, and loading. – Worked with stakeholders to gather feedback, iterating on models and data integration processes to meet evolving business requirements. CI/CD Databricks Setup: – Defined pipelines for different use cases and implemented a DevOps strategy using Databricks, IntelliJ IDE, SBT, GitHub Actions, and Jenkins. – Created a CI/CD user guide with best practices for deployment in Databricks.

– Carnet De Bord Project: – Analyzed business requirements to create technical specifications. – Designed the global architecture of the project, ensuring scalability and performance. – Ingested data into the Data Lake (Hive) from various data sources via HDFS. – Designed and built the Data Warehouse, ensuring data accuracy and accessibility. – Developed the Datamart to streamline reporting and analytics. – Developed and optimized data flows and pipelines using IBM DataStage. – Prepared editic flows to facilitate accurate reporting and data output. – Provided assistance and technical support to business lines to ensure smooth project execution. – Optimized data flows to handle high volumes of processed data efficiently. – Conseil Dans La Durée Project: – Translated business requirements into clear technical specifications. – Built end-to-end data pipelines, including: – Reading and processing files from HDFS. – Validating and controlling file schemas. – Ensuring data quality by creating Hive Views. – Developed ETL pipelines using DataStage to extract data from the Data Warehouse. – Designed and built the Datamart for the "Conseil Dans La Durée" project, inserting transformed data into DB2.

– Project: Evolution of the Decision-Making System for PRESSTALIS: – Collected and analyzed business requirements for managing business data flows related to the written press. – Created detailed specifications to guide the project development. – Designed the technical architecture and built ETL pipelines to manage data processing. – Implemented data pipelines from DB2 and various file formats using IBM DataStage. – Performed data analysis and calculated sales KPIs using Python for improved decision-making. – Set up flows to archive processed files efficiently. – Automated data pipelines using Shell scripts to ensure efficient and continuous data processing. – Sales Shops Classification Project: – Collected and analyzed business requirements for classifying sales shops according to standards. – Wrote technical specifications to guide the project implementation. – Developed data retrieval and transformation flows using DataStage. – Supported SQL queries in Business Object for reporting. – Automated pipelines using Shell scripts to streamline operations. – Migrated DataStage jobs from version 7.5.3 to 11.5, ensuring smooth transitions. – Proposed and implemented a technical solution to dynamically list jobs for migration, optimizing the process.