Data Engineer H/F

Alta Ares; Paris; Sur place; EUR 50 000 - 75 000; Plein temps

Résumé du poste

Alta Ares is seeking a pragmatic Data Engineer to design and maintain batch and near real-time data pipelines across APIs, files, sensors, and partners. You will orchestrate workflows with Prefect (or similar) and ensure reliability, scalability, and observability of data workflows in production.

You will deploy and operate data pipelines on GCP, manage data flows between storage and relational databases, and collaborate with ML teams to integrate data pipelines into ML workflows and MLOps.

Qualifications

• 2–3 years of experience in Data Engineering.
• Strong proficiency in Python for data processing.
• Solid SQL skills including data modeling and query optimization.
• Experience with PostgreSQL in production environments.
• Hands‑on experience with a workflow orchestrator (Prefect, Airflow, or Dagster).
• Experience deploying and operating pipelines on GCP or another cloud provider.
• Ability to design robust, maintainable, and scalable data pipelines.
• Experience with monitoring, debugging, and optimizing data workflows.

Responsabilités

• 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.
• 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 and cost.

Connaissances

Python

SQL

Data pipelines

Monitoring and debugging

Cloud data platforms

Outils

Prefect

Airflow

Dagster

PostgreSQL

GCP

Description du poste

About Alta Ares

Alta Ares is an air defense Neoprime. We build AI-guided interceptors to counter drones and cruise missiles, along with the software platform that powers them.

Our customers are NATO-aligned militaries and defense institutions, and our systems are regularly deployed during live exercises and operational demonstrations across Europe, the Middle East, and Asia.

Founded in 2024, we have grown to 90 people, raised over $60M, and increased revenue 40× this year. We are now entering a new phase of international expansion, industrial scaling, fundraising, and product development.

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.

Requirements

Candidate profile

You are a pragmatic Data Engineer with a strong focus on building reliable data systems in production. You are comfortable working with complex, high-volume datasets (including images, videos, and logs) and collaborating closely with ML teams in fast-paced environments.

• 2–3 years of experience in Data Engineering

• Strong proficiency in Python for data processing

• Solid SQL skills (data modeling, query optimizatio

• Experience with PostgreSQL in production environments

• Hands‑on experience with a workflow orchestrator (Prefect, Airflow, or Dagster)

• Experience deploying and operating pipelines on GCP or another cloud provider

• Ability to design robust, maintainable, and scalable data pipelines

• Experience with monitoring, debugging, and optimizing data workflows

Nice to Have

• Experience working with image or video data pipelines

• Familiarity with MLOps concepts and tooling

• Experience in constrained environments (edge computing, offline systems)

• Sensitivity to security, data governance, and defense‑related constraints