Big Data Engineer

A successful Israeli Cybersecurity and Data Analytics startup specializing in the Automotive and Connected Car sectors is expanding its engineering core. The company provides an advanced cloud platform that enables vehicle manufacturers, insurance providers, and fleet managers to monitor cyber risks and analyze complex vehicle data in real-time.

Following a successful Series C funding round with strategic backing from major industry players, the organization offers significant stability and a long-term technological roadmap.

The company is located in Central Israel (within walking distance of a major train station) and operates a hybrid work model with two days remote.

Role Overview:

• Data Platform Development: Joining a specialized team to develop and manage high-scale, AI-based data management infrastructures.
• ETL & Pipeline Engineering: Architecting and maintaining complex data pipelines using modern orchestration and processing frameworks.
• Lakehouse Architecture: Leveraging advanced storage and query engines (such as Iceberg and Trino) to optimize performance and scalability for massive datasets.
• ML Infrastructure Support: Facilitating machine learning workflows and model lifecycle management using tools like MLflow.
• Cloud-Native Operations: Deploying and scaling services within a Kubernetes environment, ensuring robust CI/CD practices.

Requirements:

• 5+ years of professional experience as a Data Engineer – Mandatory.
• Strong proficiency in Python development – Mandatory.
• Proven track record in designing and implementing complex ETL processes – Mandatory.
• Direct experience with Spark, Kafka, or Presto (Trino) – Mandatory.
• Deep mastery of SQL and large-scale data architecture principles.
• Ability to solve complex data-related challenges in a high-concurrency production environment.