Data Product and Engineering Consultant - Portfolio Analysis
Job in
New York, New York County, New York, 10261, USA
Listed on 2026-10-15
Listing for:
United Nations
Full Time
position Listed on 2026-10-15
Job specializations:
-
IT/Tech
IT Business Analyst, Data Analyst, Business Systems & Technology Analysis, Data Engineering
Job Description & How to Apply Below
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Data Product and Engineering Consultant - Total Portfolio AnalysisJob Opening
Job Opening : 286407
Job Network :
-
Job Family :
Information Management Systems and Technology
Category and Level :
Affiliate Personnel – Consultants/Individual Contractors , CON
Recruitment Type :
Consultant
Department/Office :
United Nations Joint Staff Pension Fund – Office of Investment Management
- Deliverable:
Work plan and operating cadence. - Expected output / acceptance criteria:
- Confirmed scope, timeline, stakeholders, decision points, risks, and escalation path.
- Review of the current TPV dashboard plan and recommendation for an incremental delivery approach aligned with the data platform build-out.
- Identification of key trade-offs, risks, and dependencies.
- Weekly status updates covering progress, open decisions, blockers, and next steps.
- Review and approval:
Chief of Data.
- Deliverable: TPV semantic layer and data dictionary.
- Expected output / acceptance criteria:
- Agreed definitions for each TPV data point and metric.
- Documentation of attributes, grain, formula, inputs, frequency, history, owner, lineage, and business context.
- Definitions that are clear and actionable for both business users and engineers.
- Review and approval:
Chief of Data; TPA dashboard working group.
- Deliverable:
Source assignment and Data POVs. - Expected output / acceptance criteria:
- Each mapped data point, metric, and attribute linked to an authoritative source system, dataset, and field.
- Documentation of competing sources, gaps, overlaps, conflicts, and data quality issues through Data POVs.
- Recommended source precedence and documented decision rationale.
- Review and approval:
Chief of Data; source owners.
- Deliverable:
Technical requirements and data model. - Expected output / acceptance criteria:
- Backlog-ready requirements covering:
- Data model and domain data product implications.
- Data transformations.
- Data refresh requirements.
- Data quality checks.
- Dependencies and implementation priorities.
- SQL/Python prototype logic, where useful.
- Review and approval:
Chief of Data.
- Backlog-ready requirements covering:
- Deliverable:
Dynamic TPV dashboard prototype. - Expected output / acceptance criteria:
- Interactive prototype developed in Power BI or Sigma.
- Use of source data from individual systems where available.
- Validation of dashboard direction and user interactions.
- Validation of drill-down paths.
- Identification and prioritization of production build requirements.
- Review and approval:
Chief of Data; dashboard leadership.
- Deliverable:
Handover pack and knowledge transfer. - Expected output / acceptance criteria:
- Documentation of key deliverables and decisions.
- Consolidated list of open decisions and risks.
- Implementation backlog inputs.
- Recommended next steps for the OIM team.
- Completion of knowledge transfer sessions.
- Review and approval:
Chief of Data.
- Review the current TPV dashboard plan, data inventory, and delivery assumptions.
- Recommend an incremental delivery approach aligned with the data platform build-out.
- Identify:
- Early release opportunities.
- Dependencies and sequencing choices.
- Key trade-offs.
- Priority adjustments, where needed.
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