Anais Eugene

– Led architecture choice for dbt projects, GCP resource deployment (Terraform), and implemented data quality tests (dbt test) and documentation (dbt docs, App Engine, IAM) for "Data4All" platform. – Created complex dbt incremental models for JO Paris (2024) to monitor program performance, achieving >98% precision for KPIs. – Achieved >40% cost reduction and improved daily run times for dbt models through POC and deployment of Airflow and Astronomer-Cosmos on GCP via Cloud Composer. – Transformed and enriched Lakehouse data for business insights (CRM, PowerBI) and created Python-based data export pipelines to GCS (Cloud Run). – Industrialized BigQuery table transformations (CICD/dbt/Cloud Run) and secured GCP data access. – Actively participated in agile ceremonies (Scrumban) and collaborated with Data Governance for dbt documentation integration (Collibra).

– Implemented a data pipeline for revenue metrics (DynamoDB, AWS Glue, Airflow, Cloud Storage, BigQuery, DataStudio) replacing legacy tools, saving €30k/year. – Automated PDF generation for social media diagnostics using AWS Lambda, TypeForm, HubSpot API, HighChart API, AWS S3. – Designed and automated user data integration into CRM (Hubspot) and data warehouse (BigQuery) using Segment, Batch API, Python, SQL, ETL/ELT, Webhook. – Implemented Airflow DAGs for data transformation in BigQuery and exported transformed data to Looker Studio and Google Sheets. – Monitored data quality KPIs and addressed business issues for improved results.

– Automated B2B campaign processing programs using SQL and Python. – Updated Tableau databases for clients (Mitsubishi, Mercedes). – Developed data governance rules for data reliability. – Applied agile SCRUM methodology.

– Developed ML algorithm for real-time outlier filtering on attraction wait times (PostgreSQL), achieving 95% precision for improved forecast accuracy. – Programmed a genetic algorithm (Python/Jupyter Notebook) to optimize weekly and annual workload forecasts. – Analyzed and filtered RFID card data using SQL (streaming data, sensor data, MySQL, PostgreSQL). – Optimized workload forecasts for hotels and restaurants.