Job Description

We are looking for a strong, hands-on Data Platform Engineer to join our team and play a key role in building our data infrastructure from the ground up.  
In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases.  
You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows – from ingestion to consumption.  
This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.

What will your job look like?

Design, build, and maintain the underlying infrastructure for a modern cloud-based data platform.
Implement and manage CI/CD processes for data pipelines and platform deployments across development and production environments.
Design and manage secure, scalable AWS-based data infrastructure, including IAM roles, permissions, policies, networking, and environment isolation.
Build and maintain orchestration, monitoring, alerting, and observability capabilities for data pipelines and platform services.
Support deployment, reliability, and operational excellence of data workloads running on technologies such as Spark, DBT, Airflow, Athena, and AWS services.
Collaborate closely with Data Engineers, Analysts, BI teams, and IT/Cyber teams to ensure secure and scalable data operations.
Monitor, troubleshoot, and optimize platform performance, availability, and cost efficiency.
Establish best practices for infrastructure-as-code, deployment standards, security, and production readiness.

5+ years of hands-on experience in Data Engineering, Platform Engineering, DevOps, or Cloud Infrastructure roles.
Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Strong hands-on experience with AWS, including services such as IAM, S3, Athena, CloudWatch, networking, permissions, and security policies.
Experience managing development and production environments, deployment processes, and CI/CD pipelines.
Experience supporting and operating data platforms and pipelines in production environments.
Strong understanding of data engineering concepts and modern data architectures (batch and real-time).
Experience working with Spark, Airflow, and cloud-based data processing frameworks
Strong Python and SQL skills.
Experience with monitoring, logging, alerting, and operational troubleshooting of data systems.
Experience with Infrastructure as Code tools (Terraform / CloudFormation) – Advantage
Experience with Kubernetes, containerized environments – Advantage
Experience with Kafka, Iceberg, Databricks, Snowflake – Advantage
Strong ownership and execution mindset, with the ability to work in fast-paced and ambiguous environments.
Fluent in English.

About Mobileye

Mobileye is leading the mobility revolution with its autonomous-driving and driver-assist technologies, harnessing world-renowned expertise in computer vision, machine learning, mapping, and data analysis.

Our technology enables self-driving vehicles and mobility solutions, powers industry-leading advanced driver-assistance systems, and delivers valuable intelligence to optimize mobility infrastructure. Mobileye pioneered such groundbreaking technologies as True Redundancy™ sensing, REM™ crowdsourced mapping, and Responsibility Sensitive Safety (RSS) technologies that are driving the ADAS and AV fields towards the future of mobility.

Industry

Automotive & Mobility

Company Size

1,001-5,000 employees

Headquarters

West Jerusalem, IL

Year Founded

1999

Website

mobileye.com

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