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 · Design and develop solutions for data-related technical problems and data infrastructure needs surfaced by Executive, Analytics and Design teams · 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

Competencies

? Professionalism: Knowledge of data analysis life cycle from ingest and wrangling to analysis and visualization to present findings. Knowledge of best practices and IT operations in an always-up, always-available service. Knowledge of Agile Software Development methodologies. Strong analytic skills related to working with unstructured datasets. Ability in managing and communicating data warehouse plans to internal clients. Excellent problem solving and troubleshooting skills. Working knowledge of message queuing, stream processing, and highly scalable big data stores. Process oriented with great documentation skills. Ability to convey complex / difficult data science topics to clients in a relatable manner. Takes pride in the work for the organization and understands the impact that can be brought into the organization by allowing data-driven and evidence-based decisions. Ability to apply judgment in the context of assignments given, plan own work and manage conflicting priorities. Shows pride in work and in achievements; demonstrates professional competence and mastery of subject matter; is conscientious and efficient in meeting commitments, observing deadlines and achieving results; is motivated by professional rather than personal concerns; shows persistence when faced with difficult problems or challenges; remains calm in stressful situations. ? Teamwork: Works collaboratively with colleagues to achieve organizational goals; solicits input by genuinely valuing others’ ideas and expertise; is willing to learn from others; places team agenda before personal agenda; supports and acts in accordance with final group decision, even when such decisions may not entirely reflect own position; shares credit for team accomplishments and accepts joint responsibility for team shortcomings. ? Planning& Organizing: Develops clear goals that are consistent with agreed strategies; identifies priority activities and assignments; adjusts priorities as required; allocates appropriate amount of time and resources for completing work; foresees risks and allows for contingencies when planning; monitors and adjusts plans and actions as necessary; uses time efficiently. ? Leadership: Serves as a role model that other people want to follow; Empowers others to translate vision into results; Is proactive in developing strategies to accomplish objectives; Establishes and maintains relationships with a broad range of people to understand needs and gain support; Anticipates and resolves conflicts by pursuing mutually agreeable solutions; Drives for change and improvement; does not accept the status quo; Shows the courage to take unpopular stands. Provides leadership and takes responsibility for incorporating gender perspectives and ensuring the equal participation of women and men in all areas of work; demonstrates knowledge of strategies and commitment to the goal of gender balance in staffing.

Requirements: 

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, is required. A first-level university degree (Bachelor’s degree or equivalent) in the specified fields of studies with two additional years of relevant work experience may be accepted in lieu of the advanced university degree.

Job – Specific Qualification

Not available.

Work Experience

A minimum of five years of progressively responsible experience in data management, integration, modeling, optimization and other relevant areas, 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 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 in DevOps 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 is desirable, including projects using technology such as Apache Spark, Hadoop or others. Experience in Artificial Intelligence, particularly Machine Learning techniques for data mining and extraction of large amounts of data is desirable, particularly familiarity with concepts of bias and fairness (i.e., 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 United Nations Secretariat. In addition, Arabic is a working language at ESCWA. For this position, fluency in English is required.