Alta Ares

Data Engineer H/F

🇫🇷 Paris, Francja Hybrydowo IT Pełny etat Opublikowano Maj 1, 2026
Lokalizacja Paris, Francja
Tryb pracy Hybrydowo
Forma zatrudnienia Pełny etat
Kategoria IT
Kategoria IT Inżynier danych
Język English
Opublikowano 1 maja 2026
Ostatnio sprawdzono 30 maja 2026
Kontekst JobGrid

Podsumowanie roli od JobGrid

Data Engineer H/F at Alta Ares: Paris, Francja; Hybrydowo; Pełny etat; IT; Inżynier danych. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.

  • Location and workplace: Paris, Francja, Hybrydowo
  • Role classification: IT, Inżynier danych, Pełny etat
  • Source freshness: checked by JobGrid on 2026-05-30.
  • Application path: candidates continue to the employer application page with non-personal referral tags.

About Alta Ares
Alta Ares is a deeptech startup founded in 2024, building real-time AI for defense operations (ISR, C-UAS). Our primary clients are NATO-aligned militaries, with regular deployments during live exercises. Raised €2M pre-seed in May 2025. Products include:

  • Real-time AI ISR module deployable on drones and tactical platforms
  • Counter-UAS solution enabling autonomous drone takeover under GNSS-denied environment
  • Full-stack MLOps platform for training & deploying military-grade AI models
  • Data fusion and trajectory prediction

Role & Mission

Data Pipelines & Orchestration
Design and maintain batch and near real-time data pipelines across multiple sources (APIs, files, sensors, partners). Orchestrate workflows using Prefect (or similar tools) and ensure reliability, scalability, and observability of data workflows.

Data Infrastructure (GCP)
Deploy and operate data pipelines on GCP (Compute Engine, Cloud Run, Cloud SQL, GCS). Manage data flows between object storage and relational databases, while optimizing performance, cost, and monitoring of production workloads.

Data Modeling & Storage
Design and implement PostgreSQL schemas adapted to analytical and ML use cases. Define dataset versioning strategies and ensure data quality, consistency, and traceability across systems.

ML Collaboration & MLOps Integration
Prepare and expose datasets for ML training pipelines. Guarantee reproducibility of datasets and integrate data pipelines into broader ML workflows and MLOps systems.

Security & Governance
Implement access control mechanisms and manage data permissions. Handle data classification and enforce security standards aligned with defense constraints.