Data modeler - Tenders Global

Data modeler

Food and Agriculture Organization

tendersglobal.net

<!–

Description

–>

The Statistics Division (ESS) develops and advocates for the implementation of methodologies and standards for data collection, validation, processing and analysis of food and agriculture statistics. In these statistical domains, it also plays a vital role in the compilation, processing and dissemination of internationally comparable data, and provides essential capacity building support to member countries. In addition, the Division disseminates many publications, working papers and statistical yearbooks, which cover statistics relevant to agricultural and food security relevant (including prices, production, trade and agri-environmental statistical data). The Statistics Division is involved in the management of a number of large scale projects, aimed at improving statistical methodologies and establishing best practices for the collection, collation, processing, dissemination and use of data relevant to food security, agriculture and rural areas.
ESS is also mandated to strengthen the coordination of FAO statistical activities, to monitor the implementation of statistical standards across the statistical units and to provide quality assurance to all FAO statistical processes and statistical outputs. Within this context, the SDW project on the modernization and integration of the FAO statistical system is funded by Capital expenditures Fund (CAPEX) and aims to achieve the (i) implementation of an integrated Statistical Data Warehouse (SDW) and (ii) setup a harmonized dissemination platform for FAO statistics FAODATA Explorer, both are based on SDMX (Statistical Data and Metadata eXchange) standard. 

Reporting Lines:
 

Consultants and PSA subscribers in ESS will work under the general supervision of the Chief Statistician and in close collaboration with the ESS statistician on dissemination and communication and the team leader of the SDW. They may be called upon to collaborate with other FAO Divisions and teams.
Technical Focus: 

Consultants and PSA subscribers will support the data migration from FAO databases and systems to the Statistical Data Warehouse for dissemination in the external platform FAODATA Explorer.

Tasks and responsibilities:

Consultants and PSA subscribers will contribute to and/or take responsibility for one or more of the following tasks:

  • Implement all of the necessary steps for the dissemination workflow according to the business architecture.
  • Analyze data sources and work closely with FAO data producers and data quality assurance team to harmonize and integrate data into the SDW.
  • Model statistical datasets and produce SDMX artefacts (Concept schemes, Data Structure Definitions, Code lists, etc.) according to the data producers’ requests until signoff.
  • Apply SDMX guidelines and best practices and re-use SDMX artefacts developed by other organizations in the FAO data context whenever possible.
  • Develop standard routines for data transformation to facilitate the migration of statistical databases to the SDW and support the centralized dissemination workflow, 
  • Ensure that disseminated data and metadata outputs are of high-quality and in compliance with statistical standards and data producers’ requirements.
  • Support data reporting from the FAODATA Explorer data dissemination platform to other platforms.
Candidates Will Be Assessed Against The Following:

Minimum Requirements:

  • University degree in Statistics, Data Sciences, Computer Sciences, Data Management or related disciplines
  • At least three years of years of relevant experience in the development of relational and multidimensional data models for the integration of complex databases.
  • Working knowledge (level C) of English and limited knowledge (level B) of another of the languages (Arabic, Chinese, French, Russian, Spanish) are required. For PSA subscribers only working knowledge of English is required.

<!—

<!–

–>

To help us track our recruitment effort, please indicate in your cover/motivation letter where (tendersglobal.net) you saw this internship posting.

Job Location