Data Engineer (Two Positions), P3

Org. Setting and Reporting

The United Nations Secretary-General is responsible for the investment of the assets of the United Nations Joint Staff Pension Fund (UNJSPF). This responsibility has been delegated to the Representative of the Secretary-General for the investment of the assets of the UNJSPF (RSG), who heads the Office of Investment Management (OIM). OIM manages a $100+ billion multi-asset class, global investment portfolio, with about 85% actively managed in-house. Asset classes include global equities, fixed income, foreign exchange, private equity, real estate, infrastructure, timber, and commodities. OIM staff are based in New York and come from over 40 countries.

These two positions are within the Business Intelligence Team, Data and AI Unit. The incumbents work under the technical direction of the Data Engineer (P-4) and report to the Chief of Data until the P-4 is onboarded. The team drives OIM’s data strategy, enterprise data platform and lakehouse, analytics infrastructure, reporting capabilities, and data governance frameworks to support investment and risk management decision-making.

For more information, visit OIM’s website: https://oim.unjspf.org/.

Responsibilities

• Design and develop solutions for data-related technical issues and data infrastructure needs identified in partnership with business, investment, risk, analytics, and technology stakeholders.
• Build, test, deploy, operate, and improve production data pipelines and platform components that integrate structured and unstructured data from multiple sources into the enterprise data platform and lakehouse.
• Develop data management tools for analytics, quantitative, and data science teams to help build and optimize data products.
• Apply software development lifecycle and DevOps practices, including version control, code review, automated testing, continuous integration and deployment, monitoring, incident response, and root-cause analysis, to deliver reliable and maintainable data products.
• Develop and implement changes to data systems to ensure compliance with data governance, protection, privacy, and security requirements in collaboration with key stakeholders.
• Create and maintain clear technical and business documentation alongside the code, including requirements, data models, data contracts, lineage, metadata, testing evidence, operating procedures, and decision records, so data products can be understood, governed, maintained, and extended.
• Use AI-assisted engineering tools and specialized agents, where appropriate, to accelerate and standardize activities across the data product lifecycle, with appropriate human review, testing, security, and governance controls to support reliable delivery.
• Perform other assigned duties.

Competencies

• Professionalism: Knowledge of the data engineering lifecycle from source integration and transformation through production delivery and consumption. Strong analytical skills with structured and unstructured datasets. Excellent problem-solving and troubleshooting skills. Ability to test and quality-check work before release. Process oriented with strong documentation skills, and able to explain technical work and progress in a relatable manner. Understands the impact of enabling data-driven and evidence-based decisions. Applies judgment to plan work and manage conflicting priorities. Demonstrates pride in work, professional competence, and mastery of subject matter. Conscientious and efficient in meeting commitments and observing deadlines to achieve results. Motivated by professional rather than personal concerns. Persistent with difficult problems, and remains calm under stress. Takes responsibility for incorporating gender perspectives and ensuring equal participation of women and men in all areas of work.
• Teamwork: Works collaboratively to achieve organizational goals; values others’ ideas and expertise; willing to learn from others; supports the team agenda over personal agenda; aligns with final group decisions even when they differ from personal positions; shares credit for team achievements and accepts joint responsibility for team shortcomings.
• Planning and Organizing: Develops clear goals consistent with agreed strategies; identifies priority activities; adjusts priorities as required; allocates appropriate time and resources; anticipates risks and plans contingencies; monitors and adjusts plans and actions as needed; uses time efficiently.

Education

An advanced university degree (Master’s degree or equivalent) in computer science, software engineering, data science, analytics, statistics, applied mathematics, information management, data management, information systems, information science, or a related quantitative field.

A first-level university degree (Bachelor’s degree or equivalent) combined with two additional years of qualifying experience may be accepted in lieu of the advanced university degree.

A professional certification in a cloud data platform, such as SnowPro Core or SnowPro Advanced (Snowflake), Databricks Certified Data Engineer, or an equivalent data engineering certification from AWS or Azure, is desirable.

Work Experience

• Minimum five years of progressively responsible experience in data engineering, including building, deploying, and operating production data pipelines on a cloud data platform or lakehouse.
• Production data pipeline engineering: Advanced SQL and Python skills, with the ability to design, code, test, deploy, troubleshoot, and operate production ETL and ELT pipelines on a cloud data platform or lakehouse, integrating structured and unstructured data from multiple sources.
• Software development lifecycle and DevOps: Minimum two years of hands-on experience applying software development lifecycle and DevOps practices to data products in an Agile delivery environment, including Git-based version control, code review, automated testing, continuous integration and deployment, and monitoring.
• Ability to use tools such as Azure DevOps, dbt, and Airflow, or similar, to deliver and support production data products.
• Data modelling and governance: Skills in data modelling and database design, and the ability to apply data quality, security, and privacy requirements when building or changing data systems.
• Hands-on experience building and operating data solutions on Snowflake is desirable.
• Experience with Databricks or a comparable cloud data platform is desirable.
• Experience using AI-assisted engineering tools or agents in data engineering work is desirable.

Languages

English and French are the working languages of the United Nations Secretariat. For this job opening, English is required. English must meet UN Level II for reading, writing, listening, and speaking.

Assessment

Evaluation of qualified candidates may include a hands-on technical assessment, which may be followed by a competency-based interview.

Special Notice

• This temporary job opening is for two positions available for a period of up to 364 days each and is subject to GA approval of the 2027 budget.
• Further extensions are subject to GA approval.