Data Engineer – Build Scalable Data Pipelines

About the role

Alta Ares is building AI‑guided air‑defence interceptors and needs a Data Engineer to design and operate reliable data pipelines that feed its machine‑learning models. You will work in Paris on a fast‑growing team, handling high‑volume sensor, image and video data.

Key responsibilities

• Design, develop and maintain batch and near‑real‑time data pipelines from APIs, files, sensors and partner feeds.
• Orchestrate workflows with Prefect (or Airflow/Dagster), ensuring reliability, scalability and observability.
• Deploy and run pipelines on Google Cloud Platform services such as Compute Engine, Cloud Run, Cloud SQL and Cloud Storage.
• Model and store data in PostgreSQL, supporting analytical and machine‑learning use cases.
• Prepare reproducible datasets for ML training and integrate them into MLOps pipelines.
• Implement access controls, data classification and security measures aligned with defence requirements.

Required profile

• 2–3 years of professional experience as a Data Engineer.
• Strong focus on building production‑grade data systems.
• Comfort working with large, complex datasets including images, videos and logs.
• Ability to collaborate closely with ML teams in a fast‑paced environment.

Required skills

• Python for data processing.
• SQL and data modeling expertise.
• PostgreSQL in production.
• Workflow orchestration tools (Prefect, Airflow or Dagster).
• Google Cloud Platform (Compute Engine, Cloud Run, Cloud SQL, Cloud Storage).