Tiered Approach

In line with the commitment to safeguard capacity and support personnel already in the Organization, a majority of UNDP UNCDF/UNV vacancies are advertised using a tiered application process whereby:

Tier 0: UNDP/UNCDF/UNV IP staff holding permanent (PA) and fixed-term (FTA) appointments, whose posts will be abolished, or contracts will be terminated or not renewed during 2026.
Tier 1: Other UNDP/UNCDF/UNV staff holding permanent (PA) and fixed-term (FTA) appointments
Tier 2: UNDP/UNCDF/UNV staff holding temporary appointments (TA), personnel on regular PSA contracts, and Expert and Specialist UN Volunteers
Tier 3 or no tier indicated: All other contract types from UNDP/UNCDF/UNV and other agencies, and other external candidates

Please make note of the Tier(s) indicated in the vacancy title, if any, and ensure that you satisfy the eligibility to apply.

Background

The Information and Communication Technology Section (ICTS) serves as a strategic enabler and innovation partner for the United Nations Volunteers (UNV), supporting digital transformation across the organization. ICTS provides and evolves cloud platforms, business applications, enterprise data services, cybersecurity capabilities, service management, automation, AI-enabled solutions, and a modern digital workspace for UNV.

The ICTS Data Team enables evidence-based decision-making by developing and maintaining enterprise data pipelines, data models, analytics products, governance practices, and business intelligence solutions. The role provides seasoned technical and advisory support to strengthen UNV's enterprise data platform, ensuring that data from volunteer management, HR, finance, programme, ERP, and external sources is integrated, governed, documented, monitored, and made available for reliable reporting, analytics, and emerging AI/ML use cases.

Scope of Work

The ICT Specialist - Data Engineering will provide seasoned technical leadership, subject matter expertise, platform modernization, data governance, DataOps, and analytics enablement support to UNV ICTS. The role functions as a lead technical resource for enterprise data engineering and related platform capabilities, providing technical authority through architecture guidance, engineering standards, quality assurance, and expert advisory services rather than through direct supervision of UNV personnel.

Duties and Responsibilities

A. Technical leadership, subject matter expertise, and enterprise data platform architecture

Act as a technical authority for UNV ICTS Data Teams's enterprise data engineering function, providing expert guidance on enterprise data architecture, platform design, data integration strategies, governance frameworks, and engineering standards.

Serve as UNV ICTS Data Team's technical subject matter expert for enterprise data engineering and data platform architecture, providing authoritative technical guidance for the design, evolution, modernization, and optimization of UNV's enterprise data platform, including cloud-native data pipelines, data stores, transformation frameworks, governance capabilities, and analytics enablement.

Exercise independent technical judgment, establish technical best practices, influence technology direction, and provide authoritative advice to management, stakeholders, and external service providers on matters relating to enterprise data platforms, analytics capabilities, and data governance.

Establish and maintain technical standards, architectural principles, reusable engineering patterns, and best practices to support organizational reporting, analytics, AI-enabled solutions, and data-driven decision-making.

B. Data integration, transformation, and engineering delivery

Design, develop, and optimize scalable ETL/ELT workflows to ingest, cleanse, transform, and load structured and semi-structured data from UNV source systems and external APIs into governed data stores.

Develop reusable transformation frameworks using Azure Data Factory, Databricks, PySpark/Python, SQL, Delta Lake, and related tools to ensure repeatable, idempotent, version-controlled, and performant data processing.

Implement reliable data-processing logic for batch and, where applicable, near-real-time data flows, ensuring that pipelines are resilient to source-system changes and operational interruptions.

C. Data modelling, semantic layer, and analytics enablement

Lead the design and enhancement of dimensional, normalized, and semantic data models that support operational reporting, self-service analytics, enterprise dashboards, and advanced analytical workloads.

Collaborate with business analysts, BI developers, and stakeholders to translate business requirements into trusted data products that are usable, performant, and aligned with UNV reporting needs.

Support optimization of Power BI semantic models, DAX measures, data refresh processes, and model performance in collaboration with BI colleagues.

D. Data quality, governance, lineage, and compliance

Design and implement data validation frameworks, quality checks, anomaly detection, lineage documentation, technical metadata repositories, and catalog entries to improve data reliability and transparency.

Advise on practical implementation of data governance principles, access patterns, documentation standards, and compliance-oriented controls in data engineering solutions.

Document business rules, data definitions, transformation logic, dependencies, known limitations, and data-quality thresholds for critical datasets.

E. DataOps, automation, CI/CD, and observability

Develop and maintain CI/CD pipelines for data engineering code using Azure DevOps, GitHub Actions, or similar tooling.

Implement automated testing, validation, and deployment practices across development, staging, and production environments.

Establish monitoring, alerting, and logging using appropriate observability tools to support reliable operations, incident analysis, and continuous improvement.

F. Business intelligence, reporting, and decision support

Support the design, development, optimization, and lifecycle management of Power BI reports, dashboards, data models, measures, and analytical products.

Ensure BI solutions are grounded in reliable, well-governed data and are documented through functional specifications, business rules, data model diagrams, measures, deployment pipelines, and UAT criteria.

Contribute to improved data accessibility and usability for management reporting, operational monitoring, and evidence-based decision-making.

G. Stakeholder engagement, knowledge sharing, and continuous improvement

Work with ICTS teams, business sections, data consumers, and stakeholders to identify data needs, define data-product requirements, resolve data-quality issues, and promote a data-driven culture.

Produce and maintain pipeline architecture diagrams, data dictionaries, runbooks, deployment guides, and knowledge materials.

Participate in code reviews, peer testing, engineering best-practice discussions, and continuous improvement activities.

Perform other duties within the functional profile as deemed necessary for the efficient functioning of the Office and the Organization.

Institutional Arrangement

The NPSA holder will work under the direct supervision of the Team Lead of the UNV ICTS Data Team. The incumbent will serve as a lead technical resource and subject matter expert for enterprise data engineering and related platform capabilities within UNV. The role provides technical leadership through architecture guidance, engineering standards, quality assurance, and expert advisory services.

While the position has no formal supervisory responsibility over UNV personnel, the incumbent will be expected to coordinate, guide, review, and manage the work of external vendor consultants, contractors, and technical resources engaged by UNV for data engineering, analytics, reporting, and related digital initiatives. The incumbent will provide technical direction, prioritize deliverables, review outputs, ensure quality standards, and support acceptance of vendor-delivered solutions.

The role is home-based and will work collaboratively with ICTS colleagues, data engineers, BI developers, business analysts, and business stakeholders using agreed ICTS work-management, version-control, sprint, documentation, and deployment practices.

Core Competencies

Achieve Results

Set and align challenging, achievable objectives for multiple projects, have lasting impact

Learn Continuously

Proactively mitigate potential risks, develop new ideas to solve complex problems

Adapt with Agility

Create and act on opportunities to expand horizons, diversify experiences

Act with Determination

Think beyond immediate task/barriers and take action to achieve greater results

Engage and Partner

Political savvy, navigate complex landscape, champion inter-agency collaboration

Enable Diversity and Inclusion

Appreciate benefits of diverse workforce and champion inclusivity

People Management: The position has no direct supervisory responsibilities. The role is intended to provide technical leadership and vendor/resource oversight through subject matter expertise, architecture guidance, quality assurance, and management of vendor-delivered outputs, not through line management of UNV staff.

UNDP People Management Competencies can be found in the dedicated site.

Cross-Functional & Technical competencies

Data Engineering

Ability in programming languages such as SQL, Python; ability to work with warehousing solutions and ETL tools; and understanding of basic machine learning and algorithms.

Data strategy and management

Knowledge to draft or execute a data strategy or data management framework.

Data governance

Knowledge of data science and skills to develop data management tools, organize and maintain databases, and operate data visualization technologies.

Data analysis

Ability to extract, analyse, and visualize data to form meaningful insights and aid effective business decision-making.

Data Management & Analytics

Knowledge in data management and data sciences; ability to structure data, develop dashboards and visualization, and design data warehouses, data lakes, or data-platform concepts.

Solutions Architecture

Ability to design and manage information-system architecture supporting corporate business processes and integration strategies across applications and services.

Working with Evidence and Data

Ability to inspect, cleanse, transform, and model data to discover useful information, inform conclusions, and support decision-making.

Required Skills and Experience

Education:

Advanced university degree (Master's degree or equivalent) in Computer Science, Data Engineering, Information Technology, Information Systems, Engineering (any), Mathematics, Statistics, Data Science, or a related discipline is required; or
A first-level university degree (Bachelor's degree or equivalent) in the same areas in combination with two additional years of qualifying experience will be given due consideration in lieu of the advanced university degree.

Experience:

Minimum five (5) years of relevant professional experience with a Master's degree, or
Seven (7) years with a Bachelor's degree, relevant experience should be in data engineering, cloud data platforms, business intelligence, data management, DevOps/DataOps, analytics engineering, or related ICT/data functions.

Required skills:

Proven experience designing and maintaining cloud data pipelines and ETL/ELT workflows; advanced SQL and Python/PySpark experience;
Hands-on experience with Azure Data Factory or equivalent ETL/ELT tools;
Experience with Databricks, Delta Lake, Azure SQL, data lakes, warehouses, or lakehouse architecture;
Experience implementing data quality, validation, metadata, lineage, and governance practices;
Experience with CI/CD and version control for data solutions;
Experience supporting Power BI semantic models, dashboards, and enterprise reporting.

Desired skills in addition to the competencies covered in the Competencies section:

Experience translating complex business requirements into enterprise data solutions;
Experience with Azure Functions, Container Apps, APIs, or event-driven workflows;
Experience with monitoring/observability tools such as Azure Monitor or Application Insights;
Experience with AI/ML data pipelines, feature engineering, or analytics enablement;
Experience with data privacy, access controls, and secure data engineering practices;
Experience producing architecture diagrams, runbooks, data dictionaries, and functional specifications.

Languages:

Fluency in English is required.

Other:

Candidate should demonstrate intrinsic motivation, self-direction, strong documentation discipline, and ability to work effectively in a home-based environment with reasonable overlap with Central European Time.

Disclaimer:

Only short-listed applicants will be contacted.
The successful candidate will hold a UNDP NPSA contract.
This vacancy announcement is open to Tier 1 and 2 candidates only.

Equal opportunity

As an equal opportunity employer, UNDP values diversity as an expression of the multiplicity of nations and cultures where we operate and, as such, we encourage qualified applicants from all backgrounds to apply for roles in the organization. Our employment decisions are based on merit and suitability for the role, without discrimination.

UNDP is also committed to creating an inclusive workplace where all personnel are empowered to contribute to our mission, are valued, can thrive, and benefit from career opportunities that are open to all.

Sexual harassment, exploitation, and abuse of authority

UNDP does not tolerate harassment, sexual harassment, exploitation, discrimination and abuse of authority. All selected candidates, therefore, undergo relevant checks and are expected to adhere to the respective standards and principles.

Right to select multiple candidates

UNDP reserves the right to select one or more candidates from this vacancy announcement. We may also retain applications and consider candidates applying to this post for other similar positions with UNDP at the same grade level and with similar job description, experience and educational requirements.

Use of AI by candidates

Applicants are invited to read UNDP’s guidance for candidates on using AI responsibly in UNDP recruitment and selection

Scam alert

UNDP does not charge a fee at any stage of its recruitment process. For further information, please see www.undp.org/scam-alert.

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ICT Specialist - Data Engineering (Open to Tier 1 and 2 candidates only)