The Geospatial Big Data Engineer will be involved in the design of big data solutions that leverage open source and cloud-based solutions within the Location360 enterprise initiative and will work with multiple teams across the organization (i.e. cloud analytics, data architects, business groups). The big data engineer will participate in the building of large-scale data processing systems, is an expert in data warehousing solutions and should be able to work with the latest (NoSQL) database technologies.
A big data engineer should embrace the challenge of dealing with petabyte or even exabytes of data on a daily basis. A big data engineer understands how to apply technologies to solve big data problems and to develop innovative big data solutions. The big data engineer generally works on implementing complex big data projects with a focus on collecting, parsing, managing, analyzing and visualizing large sets of data to turn information into insights using multiple platforms. The big data engineer should be able to develop prototypes and proof of concepts for the selected solutions.
Key responsibilities include:
- Understanding current and incorporating new environmental data sets
- Proactively integrating environmental data into field management systems
- Staying abreast of public domain data sets that are relevant to biotechnology pipeline.
- Partnerships within data manager communities to brings needed data sets into GIS and Big Data analytical environments
- Leadership in advancing understanding of environmental influences on field performance and risk factors.
- Minimum of 2-year experience with Hadoop based technologies such as MapReduce, Hive MongoDB or Cassandra or other NoSQL/ Big Data platform
- Minimum of 2-year experience with Geospatial Information Systems (GIS)
- Minimum of 3 years’ experience with Java, Scala, Python, or similar development language.
- Extensive knowledge in different programming or scripting languages like Java, Linux, C++, PHP, Ruby, Phyton and/or R.
- Demonstrated strong SQL skills
- Demonstrated strong Unix scripting skills
- Demonstrated experience utilizing REST, SOAP, or other data service methodologies
- Demonstrated experience adapting to new technologies
- Demonstrated knowledge of agriculture and/or agriculture oriented businesses
- Experience implementing complex big data projects with a focus on collecting, parsing, managing, analyzing and visualizing large sets of data to turn information into insights using multiple platforms.
- Capable to decide on the needed hardware and software design needs and act according to the decisions. The big data engineer should be able to develop prototypes and proof of concepts for the selected solutions.
- Experience with object-oriented design, coding and testing patterns as well as experience in engineering (commercial or open source) software platforms and large-scale data infrastructures should be present.
- Experience creating cloud computing solutions and web applications leveraging public and private API’s Qualifications
Thanks and Regards,
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