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
