National Grid (https:\\careers.nationalgridus.com)
Full Time Employee
National Grid is seeking a data engineer for their Advanced Data and Analytics team. This role will bring start-up challenges and opportunities inside a big and stable company.
The data engineer will establish capabilities to ingest big data and architect flexible and scalable data models using various open source tools as appropriate. You will develop and maintain an integrated data architecture that spans relational and NoSQL database architectures. You embrace the challenge of unraveling raw unstructured data and providing innovative solutions to our data consumers. Incumbents should be prepared to work in a highly multi-tasked environment with rapidly changing business priorities. Abilities to work cross functionally and in an Agile Team Setting are a must.
Design, construct, install, test and maintain highly scalable data management systems
Learn new data sources and determine how best to structure the data for use in advanced analyses
Research opportunities for data acquisition
Assess and resolve data quality issues and correct at source.
Ensure all data solutions meet business requirements and industry practices
Integrate new data management technologies and software engineering tools into existing structures.
Have extensive experience in employing a variety of languages and tools to marry disparate data sources
Have expert knowledge of different database solutions (NoSQL or RDBMS)
Work with leading NoSQL solutions such as MongoDB, Cassandra, etc.
Build data processing systems with Hadoop and Hadoop Ecosystems
Build scalable data pipeline solutions in a cloud environment
Build and integrate Spatial Database Platforms with front end spatial tools and other database environments
Work effectively with geospatial and GIS data and integrate it with other data
Work effectively with remote sensing and image data and integrate it with other data
Collaborate with Data Architects and IT team members on project goals
Collaborate with Data Scientists and Quantitative Analysts
Communicate effectively and translate business requirements into data solutions
Master’s degree in a data intensive discipline (Computer Science, Applied mathematics or equivalent) is strongly preferred, with a background in “big data” computer programming and/or a minimum of 3-5 years experience in “big data” processing. Additional preference would be given to a candidate with a PhD degree in a data intensive discipline. Exceptional candidates considered with Bachelor’s degree or Master’s degree in progress.
Strong programming experience with: R, Python, Java, SQL
Proven experience modeling and querying NoSQL databases
Proven experience with building and deploying ETL pipeline
Proven experience with emerging big data technologies
Building and maintaining data flow systems in AWS
Proven experience with relational databases and SQL
Plus - having geospatial and GIS skills
Plus- experience with one or more specialize areas: deep web, image and remote sensing data, natural language data
:Cust & Market Analytics
:Cust & Market Analytics
:Jan 6, 2017, 4:50:42 PM
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