Principal Data Engineer (Cortex) at Palo Alto Networks

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

09 Aug, 26

Salary

0.0

Posted On

11 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Apache Beam, Spark, GKE, Docker, Kubernetes, BigQuery, Redshift, Snowflake, SQL, Data Modeling, Cloud Data Pipelines, AI Prompting, Distributed Processing, Cloud MPP Databases, Data Lakes

Industry

Computer and Network Security

Description

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 As a Principal Data Engineer, you will be integral to the security research group, designing, building, and maintaining the data pipelines and data frameworks that are the backbone of our cyber attack detection capabilities. You will work closely with top security and AI researchers, enabling their work and seeing the direct impact of your contributions on our services and the day-to-day effectiveness of the research team. Key Responsibilities Lead the design and implementation of end-to-end, complex data pipelines and data platforms in cloud environment. Collect, analyze, and translate complex data requirements from various stakeholders including data analysts, developers, and Cyber security researchers. Develop robust, scalable Cloud based data solutions using Python and distributed processing frameworks such as Apache Beam (Dataflow) , GKE , Spark , etc. Utilize AI as part of the development cycle, including generating, reviewing, and testing code via prompts. Model and manage data within cloud MPP databases and data lakes such as BigQuery, Redshift, or Snowflake. Qualifications Required Qualifications 4+ years experience as a Senior Data Engineer / Data engineer lead (Hands-On) / Data architect - working with Cloud environments Experience in leading and implementing end to end complex Data pipelines and data platforms Experience with collecting , analyzing and syncing complex data requirements from various data users such as: Data Analysts , Developers , Researchers and Managers 4+ years Experience with Data Modeling using various Data platforms and databases 4+ years Python experience - focused on Data related areas and distributed processing (Experience with at least one of the following: Spark, GCP DataFlow (Apache Beam), GKE , etc) Experience with Docker & Kubernetes / GKE 4+ Years experience with Cloud MPP Databases / Data Lakes such as: BigQuery , Redshift , Snowflake , Azure SQL DWH , Azure Kusto Fluent with SQL AI: Using AI as part of the development cycle is second nature for you. Experience generating code via Prompts and closing the loop by reviewing and testing Experience writing MCP’s , Skills and md’s Soft skills: Collaborative Mindset: A team-first leader who believes that the best data products are built through collective genius and open communication. Bridge Builder: Naturally connects the dots between diverse teams—from DevOps to Data Science—to break down silos and streamline data delivery. Growth-Minded: Approaches feedback as a tool for evolution; possesses the grit to pivot and find the "silver lining" in complex technical setbacks. Execution Passionate: Genuinely loves the "how" as much as the "what," finding joy in the pursuit of clean code and the deployment of mission-critical pipelines. Preferred Qualifications GCP experience Data science background Cyber security knowledge Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position. Please use this form to provide us with information that will help direct your request and find your data in all of our systems

Responsibilities

Lead the design and implementation of complex end-to-end data pipelines and platforms within a cloud environment to support cyber attack detection. Collaborate with security and AI researchers to translate complex data requirements into scalable technical solutions.