Description

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 initiative

s.
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 rea

lm.
Major Responsibili

• ties
  Maintain and develop Enterprise grade Data Lake and Data Warehouse environ
• mentsCreate data infrastructure for various R&D groups across the organization that will assist them in building and optimizing our products into an innovative industry le
• ader.Work with Data Experts to assist with data-related technical issues and support their data infrastructure n
• eeds.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 c
• loud.Create and maintain optimal data pipeline archite

cture
Desired Back

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