• At least 10 years of experience in a data engineering role, including 2+ years as a Software Architect with ownership over company-wide architecture decisions.
• Proven experience designing and implementing large-scale, Big Data infrastructure from scratch in a cloud-native environment (GCP preferred).
• Excellent proficiency in data modeling, including conceptual, logical, and physical modeling for both analytical and real-time use cases.
• Strong hands-on experience with:
• Data lake and/or warehouse technologies, with Apache Iceberg experience required (e.g., Iceberg, Delta Lake, BigQuery, ClickHouse)
• ETL/ELT frameworks and orchestrators (e.g., Airflow, dbt, Dagster)
• Real-time streaming technologies (e.g., Kafka, Pub/Sub)
• Data observability and quality monitoring solutions
• Excellent proficiency in SQL, and in either Python or JavaScript.
• Experience designing efficient data extraction and ingestion processes from multiple sources and handling large-scale, high-volume datasets.
• Demonstrated ability to build and maintain infrastructure optimized for performance, uptime, and cost, with awareness of AI/ML infrastructure requirements.
• Experience working with ML pipelines and AI-enabled data workflows, including support for Generative AI initiatives (e.g., content generation, vector search, model training pipelines) — or strong motivation to learn and lead in this space.
• Excellent communication skills in English, with the ability to clearly document and explain architectural decisions to technical and non-technical audiences.
• Fast learner with strong multitasking abilities; capable of managing several cross-functional initiatives simultaneously.
• Willingness to work on-site in Ashkelon once a week.

Advantage:

• Experience leading POCs and tool selection processes.
• Familiarity with Databricks, LLM pipelines, or vector databases is a strong plus.