Data Product and Engineering Consultant - Total Portfolio Analysis

UN Secretariat; New York (NY); On-site; USD 14,760,000 - 22,140,000; Part time

Job summary

The United Nations Joint Staff Pension Fund (UNJSPF) Office of Investment Management (OIM) seeks a consultancy to define the semantic layer and reusable data products for the Total Portfolio View dashboard. You will translate business requirements into technical specs, document data meanings, and guide incremental delivery to integrate risk, performance, and liquidity data across systems.

Fluent English is essential; a Master’s degree is required, with 7+ years in data engineering or data

Qualifications

• Advanced data engineering, data modeling, or data product delivery in a complex environment.
• Experience with Total Portfolio Approach (TPA) or multi-asset analytics.
• Experience with pension fund or asset manager investment data.
• Fluent English.

Responsibilities

• Define the TPV semantic layer and data dictionary with clear meaning, attributes, grain and lineage.
• Review and complete the data inventory with the working group; identify data gaps and quality issues.
• Assign authoritative data sources across systems and document data mapping.
• Translate sourcing decisions into backlog inputs and develop technical requirements for dashboards.
• Develop SQL or Python prototypes and assess delivery sequencing for incremental implementation.
• Align stakeholders across Investment, Risk, Operations, and Data teams.

Skills

Data engineering

Data modeling

Data product delivery

Semantic layer

SQL

Python

Stakeholder alignment

Technical writing

TPA experience

Dashboard prototyping

Education

Master's degree in CS/Data Science/Engineering/Finance

Tools

Power BI

Sigma

Job description

Organizational context: The United Nations Joint Staff Pension Fund (UNJSPF) Office of Investment Management (OIM) manages a global portfolio exceeding $100 billion. OIM is initiating a Total Portfolio Approach (TPA) to manage the fund holistically, moving from separate asset class management to an integrated view. This role supports the development of a Total Portfolio View (TPV) dashboard.

Job purpose: This consultancy aims to define and establish the semantic layer and reusable data products required for the UNJSPF's Total Portfolio View (TPV) dashboard. The role involves clarifying data point meanings, identifying authoritative sources, resolving conflicts, and translating business requirements into technical specifications. The consultant will guide the development of an incremental delivery approach, ensuring the TPV dashboard aligns with the overall data platform build-out and supports the fund's strategic investment goals by integrating various data dimensions like risk, performance, and liquidity.

Responsibilities: Key responsibilities include defining the TPV semantic layer and data dictionary, ensuring clear business meaning, attributes, grain, and lineage for each data point. This involves reviewing and completing the existing data inventory with the working group. The consultant will assign authoritative data sources across systems, identify and document data gaps, overlaps, and quality issues through Data POVs. They will also write technical requirements for the TPV dashboards and semantic layer, translate sourcing decisions into backlog inputs, and develop SQL or Python prototypes. Additionally, the role involves assessing delivery sequencing, recommending an incremental implementation approach, and facilitating stakeholder alignment across Investment, Risk, Operations, and Data teams.

Education: An advanced university degree (Master's or equivalent) in computer science, data science, engineering, finance, or a related field is required. A first-level degree with additional qualifying experience may be accepted. Fluency in English is essential.

Work experience: A minimum of 7 years of advanced data engineering, data modeling, or data product delivery experience is required, with 10+ years being desirable. Direct experience with Total Portfolio Approach (TPA), total fund, or multi-asset portfolio analytics is essential. Experience with investment data from pension funds, asset owners, or large asset managers, covering public and private markets, is also required.

Skills: Data product and semantic-layer capability, data engineering, translating business to technical requirements, SQL, Python, data modeling, stakeholder alignment, clear writing, structured thinking, experience with TPA/total fund/multi-asset portfolio analytics, experience with investment data, experience mapping data definitions to source systems, experience building dashboard prototypes (Power BI/Sigma).