Sr. Graph Database Engineer (Big Data Analytics)
Palo Alto Networks® is the fastest-growing security company in history. We foster a culture of innovation, authenticity, and collaboration. This focus helps to advance our mission of protecting our way of life in the digital age. Our people make this possible. It’s in our everyday interactions, how we work together and treat each other, that sets Palo Alto Networks apart from other organizations. If you are a motivated, intelligent, creative, and hardworking individual, then this job is for you!
The Enterprise Data Governance team is a critical component of our IT Big Data Analytics team as they process petabytes of data used for key, daily business decisions. Using cutting edge technologies on distributed database systems and cloud data management, this team collaborates with other business partners to create business use cases instrumental in developing products that help move the business further such as revenue generation and marketing strategies.
We are looking for a graph database expert to build our first graph database product. This candidate should have significant knowledge and experience in graph database and graph computation areas. They must also have a passion for building high-quality enterprise-class software systems.
Experience with well-known graph database systems is highly desirable.
- Lead technical design and implementation of key components in database system products over challenging technical problems based on key customer requirements and state-of-the-art technologies.
- Mentor team members.
- Build up graph database influence by delivering valuable business use cases
- You will become part of the team behind managing the enterprise contact database.
- 5+ years working experience in building graph database systems
- Deep knowledge of key graph database technology including but not limited to graph query language, graph query optimization and processing, graph data indexing, graph data storage, graph partitioning
- Has expertise in designing and developing data management systems
- Has experience in managing Distributed and high concurrent transaction processing
- Previous experience on High availability/disaster recovery on cloud
- Cloud database performance monitoring and tuning
- Apply machine learning techniques to cloud data management
- 2+ year of experience with the Hadoop ecosystem and Big Data technologies
- 2+ years of experience with traditional RDBMS and NoSQL databases including data modeling, performance tuning and configuration
- Strong knowledge of JAVA, data structure and algorithms
- Experience in working with REST/SOAP API services
- Ability to work in a fast-paced environment and manage multiple simultaneous priorities
- Effective problem solving and analytical skills
- Past experience and knowledge around DevOps methodology
- Willingness to keep coding and setup new infrastructure from scratch
We are the global cybersecurity leader, known for always challenging the security status quo. Our mission is to protect our way of life in the digital age by preventing successful cyberattacks. This has given us the privilege of safely enabling tens of thousands of organizations and their customers. Our pioneering Security Operating Platform emboldens their digital transformation with continuous innovation that seizes the latest breakthroughs in security, automation, and analytics. By delivering a true platform and empowering a growing ecosystem of change-makers like us, we provide highly effective and innovative cybersecurity across clouds, networks, and mobile devices.
Our Security Operating Platform is built for automation. It is easy to operate, with capabilities that work together, so customers can prevent successful cyberattacks. They can use analytics to automate routine tasks, so they can focus on what matters. We are known for continuously delivering innovations; and with Application Framework, we extend that to an open ecosystem of developers that benefit from our customers’ existing investment in data, sensors, and enforcement points.
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