The United Nations Secretary-General is responsible for the investment of the assets of the United Nations Joint Staff Pension Fund (UNJSPF). The Secretary-General has delegated this responsibility to the Representative of the Secretary-General for the investment of the assets of the UNJSPF (RSG). The RSG heads the Office of Investment Management (OIM), which manages a $86+ billion multi-asset class, global investment portfolio, about 85% of which is actively managed in-house. Asset classes under management comprise of global equities, fixed income, foreign exchange, private equity, real estate, infrastructure, timber, and commodities. OIM’s staff are all based in New York and come from over 30 countries.
This position is in the Operations and Information Systems Section of the Office of Investment Management (OIM) of the United Nations Joint Staff Pension Fund (UNJSPF). The incumbent reports to an Information Systems Officer.
The focus of this position is to support effective data management. This includes building, managing, and optimizing data pipelines and architectures to support the production of analytics, in compliance with data governance, protection, privacy and security requirements. Data Engineers closely support the work of data analysts and data scientists.
Responsibilities
Within delegated authority, the Data Engineer will be responsible for the following duties:
Manage individual projects regarding the optimal extraction, transformation, and loading of data from a wide variety of sources into data pipelines, as well as the creation and maintenance of data catalogues
Managed data pipelines consist of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration to consumption for specific use cases). These data pipelines must be created, maintained, and optimized as workloads move from development to production for specific use cases. Architecting, creating, and maintaining data pipelines will be the primary responsibility of the data engineer.
Design and develop solutions for data-related technical problems and data infrastructure needs surfaced by Executive, Analytics and Design teams; and provide training in data pipelining and preparation techniques.
Manage the identification, design, and implementation of internal process improvements: automating manual processes, optimizing data delivery, re-designing architecture for greater scalability
Deploy resources to extract data features from complex datasets for data scientists and data analysts
Manage the implementation of changes to data systems to ensure compliance with data governance, protection, privacy, and security requirements
Education
Advanced university degree (Master’s degree or equivalent) in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field.
A first-level university degree in combination with qualifying experience may be accepted in lieu of the advanced university degree.
Work Experience
A minimum of five years of progressively responsible experience in data management, integration, modeling, optimization, and other relevant areas is required.
A minimum of five years of progressively responsible experience in designing data integration and pipeline architectures which must include ingesting data through different methods such as message queues, database connections, flat files, REST, or specific API’s, is required.
Experience supporting cross-functional teams and collaborating with stakeholders in support of analytics initiatives is required.
Experience in programming languages such as Python or R is required.
Experience with database programming languages (SQL, etc.) is required.
Experience in DataOps tool chains consisting of tools like Git, Jenkins or Bamboo – or equivalent tools - and experience with the deployment of data pipelines is required.
Experience in delivering big data use cases, including projects using technology such as Apache Spark, or others is desirable.
Experience in Artificial Intelligence, particularly Machine Learning techniques for data mining and extraction of large amounts of data is desirable ( i.e. familiarity with concepts of bias and fairness such as how to identify, assess, and minimize harmful biases, discrimination, and unfair outcomes in algorithmic systems and data).
Experience working with self-service analytics applications like Microsoft PowerBI, Tableau, Qlik and others for data discovery is desirable.
Languages
English and French are the working languages of the UN Secretariat. For this position, knowledge of another UN official language is desirable.
