Engineer - Oracle Big Data Cloud Service - Compute Edition
The Big Data Cloud team at Oracle is expanding its team and is in search of a seasoned 'big data' engineer to join its tight knit development team. As a senior member, you will have responsibility for implementing various features for the Big Data Cloud Service - Compute Edition (BDCS-CE) that is focused on the underlying Hadoop infrastructure. The position works closely with the rest of the team to address and implement features as it relates to the Hadoop ecosystem of services (HDFS, Zookeeper, Sqoop, Spark, Airflow, Ambari, Hive etc.).
This position requires at least a Bachelor's degree and several years of experience in distributed computing, with a strong preference for big-data related technologies. In this role, you will have the support and productivity that comes from working in a significant team of top-flight developers, partnering with product management to deliver world class enterprise software. You should come prepared to learn a lot, and define, drive initiatives in a strong team, as Oracle is on track to become the #1 provider of cloud software within the next few years, and our growth rate is spectacular.
• Research, design and implementation of new customer facing features that help expand the usability, capability and reach of the cloud service
• Address both simple and complex product defects as a part of normal development
• Translate complex functional and technical requirements into detailed design
• Facilitate knowledge sharing by creating and maintaining detailed, comprehensive documentation.
• Mentor less knowledgeable team members as needed.
• A Bachelor's degree is required in the field of Computer Science, Engineering, or related discipline. A formal degree could be waived for strong practical experience.
• Strong understanding of Hadoop and related technologies (such as Spark)
• Understanding of Hadoop related security concerns (i.e. Kerberos)
• Hadoop development and deployment experience
• Experience working in Open Source. Apache contributor and/or committer a strong plus
• At least 5 years of relevant work experience.
• At least 2 years of experience working in/with Big Data
• Engineering experience with the following technologies: Linux, Java, Scala, Python, Virtualization and Software as Service
• Strong diagnostic and analytical skills with proven skills to identify/isolate issues in complex multi-tiered Cloud deployments
• Deep understanding of common performance analysis tools and techniques
• Deep understanding and commitment to product quality
• Strong ability to learn new products and technologies
• Ability to work as an individual contributor and as a team player
• Strong written and communication and skills
• Well versed in processes around Software Development Life Cycle and Agile methodologies
Design, develop, troubleshoot and debug software programs for databases, applications, tools, networks etc.
As a member of the software engineering division, you will take an active role in the definition and evolution of standard practices and procedures. You will be responsible for defining and developing software for tasks associated with the developing, designing and debugging of software applications or operating systems.
Work is non-routine and very complex, involving the application of advanced technical/business skills in area of specialization. Leading contributor individually and as a team member, providing direction and mentoring to others. BS or MS degree or equivalent experience relevant to functional area. 7 years of software engineering or related experience.
Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.
A little about us:
Oracle is shifting the complexity from IT, moving it out of the enterprise by engineering hardware and software to work together—in the cloud.