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Data Engineer

Date: Apr 22, 2019

Location: White Plains, NY, US, 10601

Company: Bunge

Bunge Limited (www.bunge.com, NYSE: BG) is a leading global agribusiness and food company operating in over 40 countries with approximately 32,000 employees. Bunge buys, sells, stores and transports oilseeds and grains to serve customers worldwide; processes oilseeds to make protein meal for animal feed; produces edible oil products for consumers and commercial customers in the food processing, industrial and artisanal bakery, confectionery, human nutrition and food service categories; produces sugar and ethanol from sugarcane; mills wheat, corn and rice to make ingredients used by food companies; and sells fertilizer in South America. Founded in 1818, the company is headquartered in White Plains, New York.

Position Summary:

The data engineer will be an integral part of the Bunge Global Research team focusing on applying the best data engineering methodologies and practices to capture and maintain large Bunge internal and publicly available data sets for Bunge’s data scientists and analysts globally.

 

 

 

Core Functions:

Work in a cross-disciplinary project team of database specialists, data scientists, and business subject-matter experts to understand requirements and design and implement data integration solutions.

Collect available data from different sources as it relates to the business needs. Design, build, test and deploy data integration solutions to move data from Bunge’s internal systems and external data sources to Bunge’s data science and analytics platform.

Work with the information technology team to understand data capture and testing needs. Implement architecture tests and maintenance protocols.

Assess new data and sources in terms of availability and quality and clearly document findings on availability and quality of data. Build a portfolio of datasets for analysis by data scientists that will be turned into business insights.

Maintain source code repository of scripts (SQL, Python, R) provide governance and best practices of data structures, data integrity, reporting and querying.

Leverage architecture standards/patterns/API’s that will enable simple use of complex datasets

Be able to recommend and implement or help implement, ways to improve data reliability , efficiency and quality.

Help train end-users in database access and data utilization best practices as well as manage users’ issues that may arise and help solve them.  Help design dataset processes for data modeling.

Effectively communicate, through written and oral presentation, data insights to management and functional analysts.

Required qualification and skills:

 

Skills/Experience Requirements

Bachelor’s degree in Computer Science or a technical/quantitative field (e.g. engineering, statistics, physics, math, econometrics)

4+ years of experience with large-scale data management

Excellent knowledge of Oracle and other data warehouse softwards, acquaintained to SAP is definitely a plus. Excellent programming skills in shell scripting, SQL, Python, or other equivalents

Familiar with software integration using RESTful APIs

Strong communication skills, critical thinking, attention to detail, and business acumen

Preferred qualification and skills:

Proficiency in WebApp development, HTML/CSS, and Javascript/node.js

Familiarity with cloud application development, Hadoop/Spark

Familiarity with Selenium

Understanding of agronomy, remote sensing, GIS, economics, and finance is a plus

Bunge is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, citizenship, age, disability or military or veteran status, or any other legally protected status.  Bunge is an Equal Opportunity Employer. Minorities/Women/Veterans/Disabled


Nearest Major Market: White Plains
Nearest Secondary Market: New York City

Job Segment: Agricultural, Agronomy, Database, Engineer, Warehouse, Agriculture, Technology, Engineering, Manufacturing

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