Data Architect

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 Twitter, LinkedIn or Facebook.

Job Description

What you will do:

CyberArk is looking for an experienced and highly motivated Data Architect with high professional skills to join our AI, Data & Research unit.

Spearhead the development of data processes and modeling for CyberArk products; create and popularize best practices in the data field.

You will lead the development of these processes from a rich portfolio of CyberArk's services, and deliver them to production.
Work closely with software engineers and architects from the AI, Data & Research unit as well as R&D teams.
Work closely with product managers and data scientists to identify opportunities and help specify requirements for data.

#LI-OS1

Qualifications

What you need to succeed:

• 5+ years of data modeling techniques and concepts - such as Facts, Dimension, Partitions, etc.
• 5+ 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 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