Freelancer profile translated to English.

Description

Looking for a data engineer?

You are in the right place.

I have over 10 years of experience, including over 8 in data.

I have worked in various sectors such as air transport, banking, startups...

I have collaborated with companies such as Air France, Natixis, Recast.ai (now SAP Conversational AI), Hyperplan ...

I can assist you with:

• Designing, modeling, and migrating your data platform to the cloud (on AWS or GCP)

• Designing, developing, and maintaining robust data processing pipelines

• Ensuring the industrialization and production deployment of Data Science models

• Collaborating with all teams to ensure performance and reliability

• Automating Data Ops with Python, Git, Github Actions, CI/CD, Terraform

• Integrating multiple data sources (APIs, databases, files, etc.)

• Exploring your data (SQL, PIG, etc.)

• Developing MapReduce and Spark code for distributed Big Data processing

• Contributing to CI/CD improvement

• Calculating your business Key Performance Indicators (KPIs)

I also have solid knowledge of: good development practices (TDDs, unit tests, etc.), Agile (SCRUM and Kanban), web development (REST APIs), etc.

I also place great importance on transparency with my clients.

I send a daily report to my clients at the end of the day on all the tasks I have performed.

Do you have a project? Contact me, I respond very quickly.

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Data Engineer SQL, Data Engineering, Data Engineer SQL, Python AWS, Data Engineer Python, Data Engineer AWS, Dagster Pipelines, Airflow Pipelines, NoSQL, ElasticSearch, OpenSearch, Redshift, AWS RDS, AWS EC2, AWS ECS, AWS VPC, PostgresSQL, API, API Rest, FastAPI, Seaborn, Matplotlib, PyGWalker, Notebooks, Unit tests, Spark, Hadoop, Big query, Tableau, Kafka, Snowflake, ETL

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km), Lyon (up to 50km), Marseille (up to 50km), Toulouse (up to 50km), Lille (up to 50km)

Ixian.ai (SASU)
Data Engineer
TECH
April 2024 - Today (2 years and 2 months)
Paris, France
As a freelance consultant, I work for various clients on the Data Engineering side and offer services for:

• Setting up data processing pipelines
• Sourcing, collecting, and cleaning data
• Setting up data platforms in the cloud,
• Data Ops
• Data exploration and KPI calculation
• Etc.

See my profile description for more details.

Technical context: Python, Pandas, SQL, AWS, Dagster, Terraform, FastAPI, Airflow, Kubernetes, Redshift, CI/CD, OpenCV, GCP, AWS RDS, Data Engineering, Data Science, Pandas, Linux, PostgresSQL, ElasticSearch, OpenSearch, API REST, Docker, AWS ECS, TensorFlow, Shell Script, Amazon RDS, NoSQL, Spark, PySpark, Hadoop, Java

IXIAN.AI is my consulting company, through which I have had several clients paid per project, such as Promamec, Investimeo, etc.
Python API REST SQL/NoSQL Dagster FastAPI PHP Symfony Airflow Linux PostgreSQL PostGIS Elasticsearch C++ Java Docker Terraform Kubernetes Amazon Redshift Pandas CI/CD Github Actions Scikit-learn TensorFlow OpenCV Pig Django Shell Script Google Cloud Data Engineering Data science Pytorch IaC Amazon RDS Opensearch AWS CodePipeline AWS CodeBuild AWS EC2 AWS ECS
Hyperplan
Lead Data Engineer
TECH
September 2021 - December 2023 (2 years and 3 months)
Paris, France
Within the Hyperplan team, I was one of the first two employees hired to work on the company's SaaS platform. Hyperplan is a startup specializing in agricultural yield prediction to facilitate and optimize agricultural logistics. Hyperplan uses a large amount of satellite imagery to predict yield.

As Head of Software and ML Engineering, I worked on numerous data engineering, infrastructure, the first version of the API, and MLOps issues.

During my tenure, the team grew from 5 to 25 employees in 2 years. Hyperplan's clients include major names such as Axereal, Corteva, Bayer, Vivescia, etc. Hyperplan raised €4.1 million in 2023 and had an ARR of €1 million in 2023.

At Hyperplan, I was responsible for:

• Implementing the first development processes with the Head of UI/UX.
• Implementing and improving the first version of the API.
• Deploying machine learning models.
• Setting up and improving data processing pipelines.
• Implementing all CI/CD.
• Setting up all AWS infrastructure and transcribing it into IaC.
• Technical leadership and skill development for 5 new backend and data engineers.

Technical context: Dagster, Python, FastAPI, AWS, CI/CD, Terraform, Airflow, API REST, Pandas, Docker, SQL, PostgresSQL, Mlflow, MlOps, IaC, ElasticSearch,
Seaborn, Jupyter, Matplotlib, Redshift, Kubernetes, Postgis, Opensearch, AWS ECS
Platform link: www.hyperplan.fr
IaC Amazon Web Services SQL PostgreSQL Elasticsearch FastAPI CI/CD MLflow REST APIs API Dagster Airflow Python Pandas PostGIS AWS AWS S3 AWS ECS Github Actions MLOps Data Engineering Infrastructure Terraform Matplotlib Seaborn Jupyter Shell Script Heroku Docker Kubernetes Amazon Redshift
IXIAN.ai (SASU)
Data Engineer
DIGITAL AND IT
April 2018 - September 2020 (2 years and 5 months)
As a freelance consultant, I have worked for various clients on Proof of Concepts, technological consulting, software solution implementation, and training.

Among these experiences, my two largest projects were at:

1) Natixis

Natixis is a French financial institution established in 2006 and present in 40 countries. Natixis has over 13,000 employees and generates revenue exceeding 7 billion euros.

Within Natixis's data science lab, I worked on a Proof of Concept aimed at demonstrating the feasibility of an algorithm to predict company downgrades by Standard & Poor's and Moody's, based on recent company news and the detection of weak signals that might indicate an upcoming downgrade.

During this assignment, I specifically:

• Participated in source research.
• Collected, processed, and sorted data to prepare for training and testing.
• Tested various prediction approaches.
• Implemented different feature engineering approaches to improve prediction.

Technical context: Python, Pandas, NLP, Sklearn, Linux, BeautifulSoup, SQL, Data Engineering, Data Science, Data Exploration, Data Cleaning, Shell Scripts, Notebooks, CRON

2) Shanghai Solar Panel Inspection, Ltd.

At a startup specializing in the inspection of factory-produced solar panels, I contributed to developing an approach to detect solar panel cells that are inefficient and require replacement. Replacing these inefficient cells significantly improves performance.

The algorithm for detecting faulty cells was integrated into the production lines of some clients, leading to an increased detection rate of faulty panels (specific figures not available).

Technical context: Python, Notebooks, Tensorflow
Django PHP Python Data science Pandas TensorFlow Scikit-learn notebooks Pytorch Cron NLP Natural Language Processing (NLP) Jupyter Seaborn SQL Data Engineer Data Engineering Machine learning