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CONSULTANCY: Meteorological Systems Integration in Rwanda CREWS Project

Job in Campbell, Santa Clara County, California, 95011, USA
Listing for: World Meteorological Organization
Full Time position
Listed on 2025-10-16
Job specializations:
  • Engineering
    Data Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: CONSULTANCY: Meteorological Systems Integration in Rwanda for the CREWS Project
CONSULTANCY: METEOROLOGICAL SYSTEMS INTEGRATION IN RWANDA FOR THE CREWS PROJECT (SSA-2025/PDMU/DPO/MS 17)

POST

CONSULTANCY:
Meteorological Systems Integration in Rwanda for the CREWS Project GRADE

N/A DUTY STATION

Home-based, Remote COMMENCEMENT OF DUTY

31 July 2025
or as soon as possible thereafter NATURE OF APPOINTMENT

Variable (depending on needs of Department/Division)
120 days over a period of 7.5 months

ORGANIZATIONAL UNIT

Development Partnerships Office (DPO), Project Development and Management Unit (PDMU)
WMO is committed to achieving diversity and a balanced workforce. Applications are welcome from qualified women and men, including those with disabilities. The statutory retirement age after 1 January 2014 is 65. For external applicants, only those who are expected to complete the term of appointment will normally be considered.

DUTIES AND RESPONSIBILITIES

The consultant will work closely with Meteo Rwanda, WMO experts, and technology partners to achieve the following. The consultant will be responsible for:

A) Strengthen Functionality of ADL to Collect and Integrate Data from Different Sources;
- Develop and document procedures to collect AWS data from various sources, including but not limited to Vaisala, Adcon, Campbell, KOICA, and TAHMO networks.
- Develop and deploy a web-based and mobile app (forms) for remote data entry to accommodate manual ground stations and upper air stations.
- Create and update standardized stations and parameters metadata tables for both manual and upper air stations.
- Design and implement a unified relational database that integrates all incoming data, including data from manual and upper air stations.

B) Strengthen Functionality for Data Processing and Quality Control;
- Develop and enhance data aggregation routines (daily, decadal, monthly, yearly, and climate statistics).
- Develop and implement configurable and WMO-compliant quality control procedures for real-time data as well as historical observations, including:
o Syntax verification,
o Gross error checks,
o Tolerance and climatological checks,
o Internal, temporal, and spatial consistency checks.
- Expand quality control processes to support flagging, highlighting, and removing erroneous values and enable interactive review of quality control flags.

C) Add Functionality to Interface with Different Systems (Climsoft, Smart Met, WIS2, etc.);
- Develop protocols and middleware for seamless integration with in-house systems (Climsoft, Smart Met) and third-party systems such as AMSS and the WMO Information System (WIS2) via standard WMO protocols.
- Centralize climate data and metadata in a robust relational database optimized for high performance and rapid queries.
- Provide third-party data access through API clients (R and Python packages) and API URLs, enabling automated data retrieval by authorized users and applications.
- Enable web download of data and products in various formats (tables, graphs, charts, maps, JSON, CSV, Excel, NetCDF).
- Facilitate automated interaction between ADL and Climsoft, including getting and injecting data, and ensure data ingestion with wis2box and Smart Met.
- Enable automated message encoding for SYNOP, METAR, and BUFR weather messages as required.

D) Strengthen Functionality for Data Analysis and Visualizations;
- Improve and expand existing solution with aggregate menu, enabling generation of daily, decadal, monthly, and yearly reports, climate statistics, normals, extreme values, and climate indexes (e.g., CLIMDEX).
- Develop and add new climate products such as wind rose diagrams, maps, time series graphs, and heat maps.
- Design a configurable and customizable web interface allowing users to request and visualize specific variables at any time for any station, in multiple formats (graph, table, map, gridded data, etc.).
- Enable user customization for charting and reporting based on the needs of Meteo Rwanda and different user profiles.

E) Upgrade the Radar Data Processing Tool (RDT) with Additional Functionality;
- Implement and update quality control procedures for radar data, possibly including conversion to interoperable formats.
- Develop procedures for radar data processing and product…

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