What will your job look like?
- Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
- Design and implement scalable, flexible data architectures to support evolving business needs.
- Build and manage data platforms, including data lakes and data warehouses.
- Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
- Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
- Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
- Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.
All you need is:
- 5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments.
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
- Strong proficiency in Python and advanced SQL, with solid experience in data modeling.
- Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka.
- Strong experience working with AWS, including services such as S3, Athena and DynamoDB.
- Experience working with big data processing frameworks such as Spark, and columnar data formats (e.g., Parquet).
- Hands-on experience with workflow orchestration tools such as Airflow.
- Strong ownership and execution mindset, with excellent problem-solving skills and high attention to detail, and the ability to collaborate effectively and deliver in ambiguous, fast-paced environments.
- Experience with data platform technologies such as Databricks, Snowflake – Advantage.
- Experience building data platforms using modern lakehouse technologies (e.g., Iceberg) – Advantage.
- Fluent in English.
Skills Required
- 5+ years hands-on experience as a Data Engineer building data systems from scratch
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience)
- Strong proficiency in Python
- Advanced SQL and solid experience in data modeling
- Proven experience designing and building scalable batch and real-time data pipelines, including streaming technologies such as Kafka
- Experience with AWS and services such as S3, Athena, and DynamoDB
- Experience with big data processing frameworks such as Spark and columnar data formats (Parquet)
- Hands-on experience with workflow orchestration tools such as Airflow
- Strong ownership, problem-solving, execution mindset, and ability to collaborate in fast-paced environments
- Fluent in English
- Experience with Databricks and Snowflake
- Experience with lakehouse technologies such as Iceberg
What We Do
Mobileye is leading the mobility revolution with its autonomous-driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, machine learning, mapping, and data analysis. Founded in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and the RSS™ safety model. These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. Mobileye technology is used in over 170 million vehicles worldwide. In 2022, Mobileye became an independent company while still being majority-owned by Intel. Mobileye’s headquarters and R&D center are based in Jerusalem, with additional offices across Israel and around the world.
Why Work With Us
Our technology enables self-driving vehicles and mobility solutions, powers industry-leading advanced driver assistance systems, and delivers valuable intelligence to optimize mobility infrastructure.
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