Data Engineer

Company Description

About CyberArk:
CyberArk (NASDAQ: CYBR), is the global leader in Identity Security. Centered on privileged access management, CyberArk provides the most comprehensive security offering for any identity – human or machine – across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. The world’s leading organizations trust CyberArk to help secure their most critical assets. To learn more about CyberArk, visit our CyberArk blogs or follow us on X, LinkedIn or Facebook.

Job Description

What you will do:

CyberArk is looking for an experienced and highly motivated Data Engineer with high professional skills to join our AI, Data & Research unit. Spearhead the development of Data Lakehouse processes and modeling CyberArk products; Define and popularize best practices in the data field.

Work closely with ML, Data engineers and architects from the AI, Data & Research unit as well as R&D software engineering teams.
identify opportunities and help specify data requirements to improve security for CyberArk products and customers along with product managers and data scientists.

#LI-OS1

Qualifications

What you need to succeed:

• 3+ years of data modeling techniques and concepts - such as Facts, Dimension, Partitions, etc.
• 3+ years of experience in designing and implementing data ingestion, ETL processes and 3rd party tools, preferably with experience in Data Lakehouse and Data Warehouse architecture
• 5+ years of hands-on experience in SQL and Python / Pyspark (or Java / Scala)
• Data landscape understanding from vendor-specific to open-source (e.g. Snowflake/Redshift, DataBricks, Iceberg, Hadoop, DBT)
• A versatile, proactive, team player, can-do attitude, quick learner, and a great executor

How you will stand out from the crowd: 

• Data Warehouse technologies (especially Iceberg or Snowflake)
• AWS ecosystem (Glue, Athena, Kinesis, Redshift, SageMaker, EMR) – an advantage
• Experience with Data Science (Scikit-learn / TensorFlow / PyTorch, etc.) – an advantage
• Background in cyber security – an advantage
• Managerial experience in the data engineering field – an advantage