Freelancer profile translated to English.

Description

Senior Analytics Engineer, with over 5 years of experience in designing and managing end-to-end analytical platforms, from cloud architecture and dbt modeling to BI dashboard delivery and business adoption.

I translate business needs into tested and reconciled Data Marts. I specialize in four areas: multi-entity and multi-currency payment reconciliation for Finance, lead attribution for Marketing, stock distribution for Supply Chain, and omnichannel reporting for Sales.

I have rebuilt three data platforms from scratch:

Solo at Colonies: 225 dbt models in production, from Finance to Asset Management.
On legacy at Kering: a 3,000-line SQL monolith broken down into dbt models, and the Refused Store project, which reduced an annual revenue shortfall of nearly €2M by 92%.
In a startup at Connecty AI: complete stack (Snowflake, dbt, Power BI) and LLM semantic layer.

Languages

French
Native or bilingual
English
Native or bilingual
Vietnamese
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

Colonies
Senior Analytics Engineer Consultant (Data Platform & Reporting)
REAL ESTATE
March 2026 - Today (5 months)
Paris, France
Context:
Complete redesign of a European real estate operator's analytical platform: from 8 fragmented source systems to a BigQuery foundation covering Finance, Operations, Sales, Marketing, and Asset Management.
Solo mission
Key achievements:
Consolidation of Stripe payments from 35 accounts (6 entities, 4 countries) into a Finance Data Mart, validated by reconciliation and 16 automated quality tests.
Lead attribution by matching Salesforce, Pipedrive, and marketing spend, and modeling the lease and occupancy lifecycle for Asset Management reusable dimensions.
Orchestration of dbt Cloud pipelines, including 139 SCD2 snapshots for historical data, and new self-service Looker Studio dashboards.
Technical environment:
dbt (Cloud); BigQuery; Looker Studio; Fivetran; Stripe; Pipedrive; Salesforce; Typeform; Airtable; SQL; GitHub.
Looker Studio DBT Big Query Fivetran PostgreSQL
ConnectyAI
Founding AI Data Analyst
SOFTWARE PUBLISHING
December 2025 - March 2026 (3 months)
California, United States
Context:
First analytics hire at an agentic AI startup: building the internal data stack and validating the LLM-powered SQL generation engine.
Solo mission
Key achievements:
Design and optimization of the semantic layer (JSON) and marketing funnel templates, halving generation time (from 20 to 10 minutes).
LLM Benchmark (accuracy, latency, cost) through prompt engineering, guiding the choice of SQL generation engine.
Centralization of business logic in dbt: models combining Facebook Ads, GA4, and Shopify, from acquisition to revenue, and migration of Power BI transformations (DAX), now versioned and testable.
Snowflake performance and costs under control: warehouse sizing, query profile analysis, and resource monitor deployment.
Technical environment:
Snowflake; dbt; SQL; GitHub; Power BI; AI Prompting; Semantic Layer; GA4; Facebook Ads; Shopify.
Snowflake Prompt engineering semantic layer Google Analytics Big Query
Kering
Senior Analytics Engineer Consultant (Data Platform)
LUXURY GOODS
February 2023 - December 2025 (2 years and 10 months)
Paris, France
Context:
Consulting mission at Kering Technologies: modernization and scaling of the group's analytical platform (data mesh architecture) for global reporting, disseminating analytics engineering practices across Sales, Omnichannel, Supply Chain, and Marketing domains.
Team size: 14
Key achievements:
Initiated the Refused Store project: a Tableau dashboard combining OMS, Salesforce, and SAP data on in-store order refusals, leading to corrective actions that optimized stock distribution and reduced an annual revenue shortfall of nearly €2M by 92% (2022 global sales).
Aggregation of international sales from four brands with currency conversion (forex) and order lifecycle control: consolidated financial reporting and group-wide commercial KPIs.
Migration of the dbt project from AWS (Athena, S3) to BigQuery using a Medallion architecture, in line with the group's Data Mesh strategy.
Implementation of dbt controls (freshness, volume thresholds, parameter consistency) for technical tests and a Tableau monitoring dashboard for functional tests, across all pipelines: anomalies detected before reaching analysis.
Technical environment:
dbt; Tableau; Power BI; GCP (BigQuery, IAM, GCS); AWS (Athena, Redshift, S3); Git; PySpark; Airflow; Airbyte; Excel; Jira; Confluence; ServiceNow; Terraform; Docker; Manhattan OMS; GA4; Google Search Console.
DBT Tableau software AWS Google Cloud Platform (GCP) Microsoft Power BI