Description

Python engineer. I build things that run in production.

At CaseDrive I own the data platform for 20+ dental clinics — the pipelines that move clinical, financial, and marketing data from a dozen source systems into something the business can actually use. I built it end-to-end and I keep it running.

On top of that I wrap AI into the product: a system that answers questions from internal docs, agents that handle repetitive virtual-assistant work, and a scanner that reads patient forms so front desks don't have to type them in.

I pick up whatever the problem needs.

Industry field of expertise

Languages

English
Native or bilingual
French
Basic
Russian
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

CaseDrive
Python Developer
February 2024 - Today (2 years and 4 months)
Built a custom analytics platform from scratch to evaluate marketing agency performance. Gave business owners a real look into ROI, cutting through agency dashboards with clear, actionable insights. Designed and maintained FastAPI endpoints and integrated multiple third-party APIs, including medical and business services. Migrated the company's data warehouse from PostgreSQL to Databricks, unlocking faster data access and easier analytics for less technical teams. Gained hands-on experience with Spark and Databricks-native tooling. Deployed and maintained infrastructure and services across AWS (S3, RDS, Elasticsearch, Data Pipeline) and GCP (BigQuery, Cloud Functions, Compute Engine, Dataflow) — supported stability, resolved team-wide issues, and ensured platform health under evolving requirements. Created internal dashboards and a landing page to surface KPIs like appointment volume and financial performance to non technical teams.
Databricks Spark Python
Upwork
Python Developer (Freelance)
January 2023 - November 2023 (10 months)
Developed and deployed cloud-native solutions using GCP (Composer, BigQuery, Dataflow) and AWS (EC2, Fargate, Lambda, RDS, EKS). Wrote Infrastructure-as-Code using Terraform and Ansible, cutting provisioning time by 80%. Designed ETL workflows and scheduling with Airflow, optimizing data reliability and throughput. Automated crawling and scraping processes using Selenium and Scrapy, enabling structured data access from chaotic external sources. Used Docker across dev/staging/prod environments for consistent app delivery. Supported high-demand databases with scaling and performance tuning. Integrated LLMs into automation pipelines and feature enhancements. Set up CI/CD pipelines using GitHub Actions, significantly accelerating deployment cycles.