Company Name:-
Palo Alto Networks

Job Location:-
Bengaluru, Karnataka

Job Summary:-
Company Description
Our Mission
At Palo Alto Networks®, everything starts and ends with our mission:
Being the cybersecurity partner of choice, protecting our digital way of life.

We have the vision of a world where each day is safer and more secure than the one before.

These aren’t easy goals to accomplish — but we’re not here for easy.

We’re here for better.

We are a company built on the foundation of challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.

Job Description
Your Career:
Palo Alto Networks is looking for a Senior Quality Engineering Data Analyst for the Hardware Quality Engineering team.

This individual will work collaboratively with the HW Engineering, Global Customer Support, Hardware and Software Engineering, and Technical Operations teams extracting and displaying trends, inflections, commonalities, anomalies, and so forth, from corporate data sources enabling proactive, accurate decisions by internal stakeholders supporting excellent customer satisfaction.

Your Impact:
Continually search applicable data sources about Palo Alto Networks products for useful information about designs, processes and problems.

Manually search using ad hoc queries.

Develop, document and deploy automation you develop to complete repetitive tasks,
Organize and display information you have found in easily consumable formats for various corporate audiences (e.

g HW and SW engineering, operations, management) highlighting and prioritizing positive and negative product and process characteristics.

Improve data quality by feeding forward data input, format and structure requirements to Quality Engineering and Information Technology teams in ways that enable improved data access and information access.

Join data from various sources such as:
New product introduction test
Production (Test Yields, paretos and component dppm)
Field (Customer Returns data/symptom paretos, Customer Failure Logs data error message paretos, Telemetry data, normalized product return trends)
Failure analysis and Repair (Findings and normalized trends, including component FIT rates)
Change management (identify or refute inflections due to hardware

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