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# Data Engineer (Two Positions), P3

- **Company:** United Nations
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Code Review, Information Systems, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Database Design, DevOps, Information Management, Information Sciences, Python (Programming Language), Operational Databases, Software Tools, Software Engineering, Unstructured Data, Enterprise Data Management, Cloud Platform System, Sql Optimization, Snowflake, Data Strategy, Git, Information Technology, Data Analytics, Data Management, Software Version Control, Data Pipelines, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=94213dc00fbf6a3a

## About the Role

* Professionalism: Knowledge of the data engineering lifecycle from source integration and transformation through production delivery and consumption. Strong analytical skills related to working with structured and unstructured datasets. Excellent problem-solving and troubleshooting skills. Ability to test and quality-check own work before release. Process oriented, with strong documentation skills. Ability to explain technical work and progress to clients in a relatable manner. Understands the impact of enabling 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 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. Takes responsibility for incorporating gender perspectives and ensuring the equal participation of women and men in all areas of work. * 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 the team agenda before the personal agenda; supports and acts in accordance with final group decisions, even when such decisions may not entirely reflect one's own position; shares credit for team accomplishments and accepts joint responsibility for team shortcomings. * Planning and Organizing: Develops clear goals that are consistent with agreed strategies; identifies priority activities and assignments; adjusts priorities as required; allocates an 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.
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) in combination 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.
Job - Specific Qualification
Not available.
Work Experience
A minimum of five years of progressively responsible experience in data engineering, including building, deploying and operating production data pipelines on a cloud data platform or lakehouse, is required. 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 is required Software development lifecycle and DevOps: A minimum of 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 is required. Ability to use tools such as Azure DevOps, dbt and Airflow, or similar, to deliver and support production data products is required. 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 are required. 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. The table below shows the minimum required level for each skill in these languages, according to the UN Language Framework (please consult https://languages.un.org for details).

## Description

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 $100+ billion multi-asset class, global investment portfolio, about 85% of which is actively managed in-house. Asset classes under management comprise global equities, fixed income, foreign exchange, private equity, real estate, infrastructure, timber and commodities. OIM's staff are all based in New York but come from over 40 countries. For more information, please visit OIM's website at https://oim.unjspf.org/. These positions are located in the Business Intelligence Team, Data and AI Unit. The incumbents work under the technical direction of the Data Engineer (P-4) and reports to the Chief of Data until the P-4 is
onboarded. This team leads 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.
Responsibilities
Within delegated authority, the Data Engineers may be responsible for the following duties: * Design and develop solutions for data-related technical problems 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 better 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 that 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, while applying appropriate human review, testing, security and governance controls to ensure reliable delivery. * Performs other assigned duties.