Data Engineering Consultant

vor 1 Woche

Home Office, Schweiz International Telecommunication Union (ITU) Vollzeit

INTERNATIONAL TELECOMMUNICATION UNION

  • ITU is the leading United Nations agency for information and communication technologies, with the mission to connect the world. To achieve this, ITU manages the radiofrequency spectrum and satellite orbits at the international level, works to improve communication infrastructure in the developing world, and establishes global standards that foster seamless interconnection of a vast range of communication systems._

Data Engineering Consultant

Vacancy notice no: 1308

Sector:

BDT

Department:

DNS

Country of contract:
Remote

Duty station:
Home Based

Position number:
positionNumber

Grade:
PositionGrade

Type of contract:
Consultant

Duration of contract: 6 months

Recruitment open to:
External

Application deadline (Midnight Geneva Time): 7 August 2023

ORGANIZATIONAL UNIT


The Telecommunication Development Bureau (BDT) is responsible for the organization and coordination of the work of the Telecommunication Development Sector (ITU-D) of the Union which deals mainly with ICT-focused development policies, strategies and programmes, as well as technical cooperation activities, to promote digital inclusion and drive digital transformation at community, country and regional levels.

To effectively and efficiently serve the needs of ITU members,
BDT is organized into four functional areas:

  • Office of the Deputy to the Director and Field Operations Coordination Department
  • Partnerships for Digital Development Department
  • Digital Networks & Society Department
  • Digital Knowledge Hub Department

TERMS OF REFERENCE:

  • Collect, import, and clean large volumes of unstructured and structured data from various sources related to telecommunications and ICT infrastructure. Develop, construct, test, and maintain data architectures to ensure their streamlined operation.
  • Implement methods to standardize and validate data to maintain consistency and accuracy. Implement tools and frameworks for data validation, cleaning, and preprocessing.
  • Develop and generate data quality reports. Design and implement robust data quality checking techniques to ensure high data accuracy and reliability.
  • Design, construct, install, and maintain highly scalable data management systems. Create complex queries and scripts for data manipulation and analysis.
  • Develop and maintain an automatic reporting system to generate relevant reports. Ensure the integrity and security of data in the reports.
  • Work closely with data scientists and other team members to integrate data with existing models. Collaborate with various teams to support their data infrastructure needs.
  • Develop and integrate datadriven dashboards for business intelligence reporting. Visualize data insights in a userfriendly manner.
  • Construct and maintain an opensource automatic pipeline to streamline data operations, ensuring optimal functionality of all data systems.
  • Develop and maintain an effective and scalable file and folder structure to ensure data is easily accessible and properly secured.
  • Document procedures and practices in a clear and structured manner to ensure knowledge transfer, compliance, and future scalability.
  • Stay updated with the latest technology trends in data engineering, data science, and related fields, bringing in new ideas to continuously improve the data infrastructure.

CONCRETE DELIVERABLES:


A data collection and ingestion system capable of collecting, importing, and cleaning large volumes of unstructured and structured data from various sources.


  • Implement and document methods and procedures for standardizing and validating data to ensure consistency and accuracy.
  • Regularly generated reports that assess the quality and integrity of the data being managed, with clear metrics for evaluation.
  • An automated system for generating necessary reports related to the data.
  • Datadriven dashboards integrated for business intelligence reporting, showcasing key insights from the data in a visually intuitive manner.
  • Tools and systems for seamless integration of data with existing models and across various teams.
  • A wellconstructed opensource automatic pipeline that streamlines data operations and can be used by others in the community.
  • An optimized, scalable, and secure file and folder structure that ensures data is easily accessible and wellorganized.
  • Detailed documentation outlining data management and processing practices, procedures for using the data pipeline, and other systems created. This should include clear instructions for replicating and scaling these systems.

COMPETENCIES:

Technical Competencies:

Knowledge of design and implementation of automated data pipelines; Technical knowledge in Python, SQL, Git, PostgreSQL, Microsoft Azure, Amazon Web Services, Docker, Kubernetes, Apache Airflow, etc.


QUALIFICATIONS REQUIRED:

Education:
University degree in Computer Science, Data Science, Data Engineering, Telecommunications, o

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