Data Engineer

An established Israeli AI & Data technology center operates as a high-agility R&D unit within a major global corporation.

The center specializes in the PropTech domain, building sophisticated AI and LLM-based solutions to drive predictive insights and large-scale investment decisions.

Combining a startup-like culture with the vast resources and immense data repositories of a global parent company, the unit focuses on transforming complex market data into actionable intelligence.

Located in Central Israel (prime location with excellent train access), the center offers a highly flexible hybrid work model with three days remote flexibility.

This environment provides a unique opportunity to work on cutting-edge GenAI and Machine Learning projects at an enterprise scale, ensuring both rapid innovation and long-term stability.

Role Overview:

• Data & AI Infrastructure: Taking a lead role in designing and operating high-scale production infrastructures for both Data and AI systems.
• Pipeline Engineering: Architecting and implementing robust Data and ML/AI pipelines, including complex ETL/ELT orchestration and model versioning.
• GenAI Production: Building scalable and reliable foundations for GenAI and RAG (Retrieval-Augmented Generation) systems, ensuring observability and high availability.
• Big Data Orchestration: Developing and managing Spark-based pipelines and leveraging advanced cloud platforms such as Databricks.
• MLOps & Automation: Establishing CI/CD processes, GitHub Actions, and monitoring frameworks for Large Language Models and predictive systems.
• Cloud-Native Deployment: Deploying and managing services across multi-cloud environments (AWS/GCP/Azure) utilizing Kubernetes.

Requirements:

• 3+ years of experience in Data Platform Engineering, Data Engineering, or MLOps – Mandatory.
• Programming Mastery: Expert-level proficiency in Python – Mandatory.
• Cloud Infrastructure: Proven experience with major public cloud providers (AWS, GCP, or Azure) – Mandatory.
• Advanced AI Knowledge: Hands-on experience with ML, LLM, RAG, and Agent platforms – Mandatory.
• Professional Pedigree: Proven track record in reputable, high-tier technology companies – Mandatory.
• Academic Foundation: B.Sc. in a technological field (Computer Science/Engineering), preferably from a leading university – Mandatory.