Data Engineer

Why Join Us?

We are looking for a talented Data Engineer to join our development team in the big data platform group.

You will support our data scientists on data initiatives, expand our data, and optimize our data pipeline architecture. You must be self-directed and comfortable supporting the data needs of multiple systems and products. The right candidate is excited by the prospect of building the data architecture for the next generation of products and data initiatives.

This is a unique opportunity for you to be a member of a team full of outstanding people making a big impact on Check Point. We work on multiple products in many domains to deliver truly innovative solutions in the Cyber Security and Big Data realm.

Key Responsibilities

• Maintain and develop Enterprise grade Data Lake and Data Warehouse environments
• Create data infrastructure for various R&D groups across the organization that will assist them in building and optimizing our products into an innovative industry leader.
• Work with Data Experts to assist with data-related technical issues and support their data infrastructure needs.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources on top of Azure cloud.
• Create and maintain optimal data pipeline architecture

Qualifications

• B.Sc. in Computer Science, Computer Engineering or a similar degree.
• 3+ years of experience as a Software or Data Engineer working on production systems.
• Proven experience in Apache Spark using Python or Scala.
• Advanced working SQL knowledge and experience working with relational databases.
• Experience building, optimizing and automating, data pipelines, architectures and data sets.
• Strong project management and organizational skills.
• Advantage - Azure cloud Services: Storage Accounts, EventHub, DataBricks.