Data Engineer H/F

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

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