Data Platform Engineer

Mobileye, an Intel Company

Mobileye, an Intel Company

Posted on May 20, 2026
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.