Data Engineer

An Israeli-founded technology company provides a cloud-native cybersecurity and data analytics platform specifically designed for the automotive and connected car industries.

The company develops advanced systems to protect vehicles and optimize data flows for global car manufacturers, insurance providers, and fleet management firms.

Following a successful Series C funding round with over $100M in total capital raised, the company maintains a stable financial position and a significant global footprint.

The company is located in Central Israel (short walk from the train station) and operates a hybrid work model with two days remote flexibility.

Role Overview:

• Data Management Leadership: Joining the engineering team responsible for building an advanced, AI-driven Data Management platform.
• Large-Scale ETL: Designing and implementing complex ETL pipelines to process massive volumes of telematics and security data.
• Modern Data Stack: Developing with Python, utilizing Prefect for orchestration, and Trino for high-performance querying.
• Data Lakehouse Architecture: Working with Apache Iceberg and SQL to manage structured and unstructured datasets at scale.
• MLOps Integration: Supporting the lifecycle of AI models by integrating tools like MLflow into the data infrastructure.
• DevOps & Scaling: Deploying and managing services within Kubernetes environments using GitHub Actions for CI/CD.

Requirements:

• 5 years of professional experience as a Data Engineer – Mandatory.
• Expertise in Python development – Mandatory.
• Proven track record in building and optimizing ETL pipelines – Mandatory.
• Hands-on experience with Spark, Kafka, or Presto/Trino – Mandatory.
• Deep understanding of data modeling, data warehousing, and distributed systems.
• Experience working in high-scale, production-grade cloud environments.