Siemens Recruitment of Research Engineers- Data Centric Systems
Job Role: Research Engineer- Data Centric Systems
Qualification: Masters / PHD Degree in Computer Science
Job Responsibility: Performing research, development and consultancy projects
Job Location:: Bangalore
Job Type : Regular Full Time
Skills: Cloud computing, hadoop, large scale graph processing systems, in-memory computing
Salary Offered Best in the Industry
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Research Engineer (Data-centric Systems) (132264)
Req ID 132264 - Posted 08/01/2013 - India - Bengaluru - Corporate Units - Information Technology - Early professional (1 - 3 years) - Siemens Employee - Full time only
Job Title - Research Engineer(DataCentric Systems)
Location: Bangalore
Job ID:132264
Introduction
With over 1,900 research operatives worldwide, the Corporate Technology department (www.ct.siemens.com) occupies a special position within Siemens' R&D facilities. It functions as an international network of expertise and as a global partner for technology and innovations. Through its R&D activities in Germany, the USA, China, India, Russia, Japan and Eastern Europe Corporate Technology helps secure the company's technological future and bolster its competitiveness.
RTC is at the heart of Siemens R&D. Its strong technology base makes it a strong in-house partner for innovation. We develop technologies with wide applicability for the Siemens Divisions and help them to successfully bring innovations to market. Our about 1,800 scientists at locations in North America, Europe, and Asia ensure the technological and innovative future of the company.
Every software-centric system deals with data. Structure and volume of the data and the architecture of program components decide the quality of the end-product. We address innovational challenges in developing architectures for systems that need to acquire, store, and process high volume data of varying complexity while guaranteeing quality attributes such as scalability, availability, reliability and performance.
Our research primarily focuses on High-volume data stores, online/stream processing and offline/batch processing mechanisms and technologies.
What are my responsibilities?
Performs research, development, and consultancy projects in close teamwork with colleagues, customers, and universities.
Performs architecture reviews and assessments.
Performs development and implementation of customized solutions for the Siemens operating companies.
Extracts architecturally-significant requirements, and ensures feasibility of these requirements.
Makes architecturally-significant design decisions at the right level of abstraction.
Defines, articulates and applies architectural principles and patterns.
Documents and communicates architectures.
Develops strategies for risk mitigation, including risks associated with unstable requirements.
Provides technical leadership to the team, collaborators, and customers.
Is aware of state-of-the-art software architecture methods, tools, and trends.
Identifies high-impact research topics in software architecture.
Presents proposals, concepts, and results to collaborators and customers.
Writes papers for presentation in journals and conferences.
Supervises the work of graduate student interns.
Acquires and leads projects.
Travels to meet with collaborators and customers.
What do I need to qualify for this job?
Masters degree in Computer Science, Electrical Engineering, or a related discipline.
Ph.D. desired.
Extensive knowledge about the use of architectural/design patterns, UML, and other modeling languages.
Experience with object-oriented analysis, object-oriented design, and object-oriented programming.
Strong problem solving, communication and team working skills.
Strong background in data management concepts and technologies is desirable.
Research experience in the broad field of data management preferred.
Knowledge of distributed computing highly desirable.
Hands-on experience with one or more of the following is highly desirable:
Big Data/NoSQL storage, Key-value stores (e.g., Cassandra), document stores (e.g., MongoDB)
Cloud computing (Microsoft Azure/Amazon EC2)
Distributed data processing technologies
Hadoop stack
CEP/Data stream processing platforms (e.g. StreamInsight, Oracle CEP, Storm)
large-scale graph processing platforms (e.g., pregel)
In-memory computing (e.g. spark)
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