Question 1

Which Data & AI freelance profiles are available at Todai?

Accepted Answer

Todai covers 6 specialized profiles: Data Engineer, Analytics Engineer, MLOps Engineer, Platform Engineer, Cloud Engineer and AI Engineer. All profiles come from the top 5% of the freelance market, with at least 3 years of experience on their main stack. Daily rates range from €600 to €1,200 depending on the profile and seniority.

Question 2

How can I filter Data freelancers by availability?

Accepted Answer

The Todai network lets you filter by availability (immediate, within 2 weeks, within 1 month, within 3 months), by role (Data Engineer, MLOps, Platform, etc.), by technical stack (Snowflake, dbt, Airflow, Python, Kubernetes, AWS, GCP, Azure...) and by seniority (3 to 12+ years). To receive a shortlist of 3 profiles that match your need exactly, send us a brief: we reply within 48 hours.

Question 3

What is the average daily rate of a freelance Data Engineer in France?

Accepted Answer

In 2025, the daily rate of a freelance Data Engineer in France is between €550 and €850 for profiles with 3 to 8 years of experience. Lead or Architect profiles often exceed €900 per day. MLOps and AI Engineer specializations are the most valued, with daily rates that can reach €1,000 to €1,200 for senior profiles. Profiles in the Todai network are at the top of these ranges. They belong to the top 5% of the market.

Question 4

How many Data freelancers are in the Todai network?

Accepted Answer

The Todai network brings together technically validated Data & AI freelancers, selected through a structured interview, architecture tests and practical cases on their stack. Only the top 5% of candidates join. Profiles cover 6 specializations (Data Engineer, Analytics Engineer, MLOps, Platform, Cloud, AI Engineer) across the Modern Data Stack and generative AI.

Question 5

What technical stack do Todai network freelancers cover?

Accepted Answer

Todai freelancers command the full Modern Data Stack: orchestration (Airflow, Dagster), transformation (dbt, Spark), storage (Snowflake, BigQuery, Databricks, Redshift), cloud (AWS, GCP, Azure), infrastructure (Kubernetes, Terraform, Docker), MLOps (MLflow, Kubeflow, Ray) and generative AI (RAG, LLM, MCP, A2A agents). Each profile is assessed on their declared stack before joining the network.