Data Engineer (Data & AI solutions)
About the role
Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.
Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary IDIRA by Palo Alto Networks is looking for an experienced and motivated Data Engineer with high professional skills to join our AI and Data Solutions unit. Spearhead the development of Data Lakehouse processes and modeling CyberArk products; Define and popularize best practices in the data field. Working closely with business entities such as sales and product from IDIRA organization, along with data science and data analytic from the AI and Data Solutions unit. identify opportunities and help specify data
requirements to improve on boarding, sales, and security for Idira products and customers along with product managers and data scientists. Key
Responsibilities Own the end-to-end design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems. Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT. Apply advanced data modeling techniques to structure complex data assets into optimized facts, dimensions, and partitions. Partner closely with cross-functional leadership across data science, analytics, R&D, and IT teams to identify data