Data Product and Engineering Consultant - Total Portfolio Analysis

This consultancy position is located in the Office of Investment Management of the United Nations Joint Staff Pension Fund. The consultant will lead the Total Portfolio Approach (TPA) analytics and data product delivery, including semantic layer definition, source assignment, technical requirements, dashboard prototyping, and stakeholder facilitation.

Responsibilities

• Review and complete the existing TPV data inventory with the working group.
• Define each TPV data point or metric with clear business meaning, attributes, grain, formula, inputs, frequency, history, owner, lineage and decision rules.
• Identify reusable domain data product implications underneath TPV, including where common definitions, attributes or source data should support more than one dashboard or use case.
• Assign each mapped definition to its authoritative source across systems, including but not limited to Northern Trust, Bloomberg, MSCI Barra One, Burgiss and internal registers, as applicable.
• Identify gaps, overlaps, conflicts and data quality issues.
• Produce Data POVs, meaning short decision papers that compare source options for the same metric or attribute, including definition differences, calculation logic, timing, data quality, lineage, recommended source and decision rationale.
• Write technical requirements for the TPV dashboards and supporting semantic layer, including data model, transformations, source precedence, refresh needs, data quality checks and implementation dependencies.
• Translate sourcing decisions and domain data product implications into prioritized inputs for the data platform delivery backlog.
• Develop SQL or Python prototype logic where useful to validate data modelling assumptions or make requirements executable for the OIM engineering team.
• Assess the current TPV dashboard plan, sequencing and delivery assumptions based on data availability, source readiness, semantic-layer complexity and implementation dependencies.
• Recommend an incremental delivery approach that aligns TPV outputs with the data platform build-out, including what can be delivered early, what depends on platform capabilities, and which decisions or dependencies need to be resolved first.
• Identify and document key trade-offs, including speed versus quality, prototype versus production readiness, available source versus authoritative source, short-term workaround versus reusable data product, and dashboard priority versus data platform dependency.
• Build or guide a mock-up of an active, dynamic TPV dashboard in Power BI or Sigma, using source data from individual systems where available.
• Make the prototype interactive, with filters, changeable variables and drill-down paths rather than static charts.
• Use the prototype as a proof point to validate semantic-layer decisions, dashboard direction and production build priorities.
• Facilitate working sessions, meetings and decision discussions across Investment, Risk, Operations, the TPA dashboard working group and the Business Intelligence Team.
• Drive alignment where the same metric or attribute has different meanings across teams or systems.
• Share practical approaches, lessons learned and best practices from comparable TPA, total fund or multi-asset portfolio analytics implementations.
• Join the weekly TPA dashboard working group and give a short written status update each week.
• Be available for regular on-site meetings, working sessions and stakeholder discussions in New York, as required.
• Must not share project details without written consent from UNJSPF, and must follow OIM data classification and information security rules.

Requirements

• Advanced university degree (master's or equivalent) in computer science, data science, engineering, finance or a related field. A first-level degree with additional qualifying experience may be accepted instead.
• Minimum 7 years of advanced data engineering, data modelling or data product delivery experience is required; 10 years or more is desirable.
• Direct experience with TPA, total fund, or total portfolio / multi-asset portfolio analytics, including total fund exposure, factor, risk, performance and liquidity views is required.
• Experience with investment data at a pension fund, asset owner or large asset manager, covering public and private markets is required.
• Proven experience mapping data definitions to source systems and writing technical requirements is required.
• Experience translating business use cases into reusable data product requirements, source decisions and implementation priorities is required.
• Experience facilitating business and technical alignment across functions where definitions, source choices or implementation priorities require agreement is required.
• Experience building or guiding interactive dashboard prototypes (Power BI and/or Sigma) from multiple sources is required.
• Ability to work across business lines and explain data topics clearly to non-technical senior stakeholders is required.
• SQL and Python; data modelling, semantic layer design, data warehouse and cloud data platform experience is required (Snowflake is an advantage).
• Power BI and/or Sigma is desirable.
• Familiarity with Bloomberg, MSCI Barra One, Burgiss, and custodian or accounting data is desirable.
• Fluency in English is required.

Skills

• Data Engineering
• Data Modelling
• Data Product Delivery
• Total Portfolio Analytics
• Investment Analysis
• Data Definition Mapping
• Technical Requirements Writing
• Business Use Case Translation
• Multi-Stakeholder Facilitation
• Dashboard Prototyping
• Power BI
• SIGMA
• SQL
• Python
• Semantic Layer Architecture
• Data Warehouse
• Cloud data platforms
• Snowflake

Languages

English