HR Analytics: Power BI Talent Acquisition Dashboard

About the project

Power BI – Talent Acquisition Control Tower & Executive Dashboard We are looking for an experienced Power BI Developer / HR Analytics Specialist to build a comprehensive Talent Acquisition Control Tower & Executive Dashboard. This is not a basic visualization project. We need a scalable recruitment analytics solution covering the full recruitment lifecycle: Requisition → Sourcing → Screening → HM Review → Interview → Selection → Offer → Acceptance → Joining → Closure The solution must support both daily recruitment operations and executive-level reporting. 1. Recruitment Overview & Demand vs Delivery Track: * Total Requisitions * Total Openings/Vacancies * Open / Closed / Hold / Cancelled * Sourcing / Interview / Offer / Joining stages * Joined * Under Joining * Remaining Vacancies * Hiring Completion % * Critical Vacancies * Active Pipeline * SLA & Aging Important: distinguish between number of requisitions and number of openings/headcount. Required analysis: Openings → Joined → Under Joining → Remaining → Completion % with drill-down by BU, Project, Location, Department, Position, Recruiter and Requisition. 2. Recruitment Pipeline & Funnel Track: Sourced → Screened → Submitted → Shortlisted → Interviewed → Selected → Offered → Accepted → Under Joining → Joined Calculate conversion rates, rejection/dropout rates, Offer Acceptance Rate and Acceptance-to-Joining Rate. The dashboard should identify where candidates are being lost or delayed. 3. SLA & Aging Include: * Time to Fill * Time to Hire * Time to Offer * Time to Join * Requisition Aging * Stage Aging * Approval → First CV * CV → HM Feedback * Feedback → Interview * Interview → Offer * Offer → Acceptance * Acceptance → Joining * SLA Compliance % * Within SLA / Approaching SLA / Breached SLA SLA rules should be configurable where possible. 4. Daily Recruitment Control Tower / Action Center A key requirement is a daily action page showing exactly what is delayed and who owns the next action. Examples: * No sourcing activity * No CV submitted * HM feedback pending * Interview scheduling/feedback pending * Selection pending * Offer/approval pending * Candidate acceptance pending * Delayed joining * SLA approaching/breached * No recent activity * Missing recruitment data Display: Req | Position | Project | Location | Recruiter | Stage | Pending Action | Action Owner | Days Pending | SLA | Priority The dashboard should answer: What is delayed? Why? For how long? Who owns the action? 5. Recruiter Performance Measure: * Assigned Requisitions/Openings * Active Workload * CVs Submitted * Interviews * Selections * Offers * Accepted Offers * Joined * Remaining * Completion % * Time to Fill * Aging * SLA Compliance * Conversion * Offer Acceptance * Productivity * Data Quality * Monthly Trend Performance should consider workload + delivery + speed + SLA + quality, not only number of hires. 6. Hiring Manager Performance Measure: * CV Feedback Pending * Average Feedback Time * Interviews/Feedback Pending * Selection/Approval Pending * HM SLA Compliance * Days Delayed * Response Rate * Hiring Completion The solution should clearly differentiate TA delays from Hiring Manager/Business delays. 7. Offer & Joining Analytics Track: * Offers Issued / Accepted / Declined / Pending * Offer Acceptance Rate * Under Joining * Joined * Delayed Joining * Withdrawals * Acceptance-to-Joining % * Average Time to Join * Expected Joining / Joining Forecast 8. Source Performance Analyze sourcing channels such as LinkedIn, Referral, Database, Job Portals, Direct Sourcing, Agencies, Career Website, etc. Measure candidates, shortlisted, selected, offers, joins and conversion/quality by source. 9. Project / Location Analysis & Critical Vacancies For every BU / Project / Location / Department / Position show: Openings | Joined | Under Joining | Remaining | Completion % | Pipeline | Aging | SLA | Critical Vacancies | Pending Actions Highlight: * Critical positions * High aging * SLA breaches * Positions without candidates * Weak pipelines * Offers/joining at risk * No recent activity Use Green / Amber / Red (RAG) indicators. 10. Recruitment Quality & Data Health Monitor: * Missing mandatory fields * Duplicate records * Missing dates * Incorrect/inconsistent statuses * Stale requisitions/candidates * Missing Recruiter/HM/Project/Location * Data Completeness % * Overall Recruitment Data Health Score Users should be able to drill into records requiring correction. 11. Global Filters & Dynamic Interactivity Mandatory global/synchronized filters: Year | Quarter | Month | Week | Day/Date | BU | Project | Location | Department | Position | Grade | Recruiter | Hiring Manager | Req Status | Stage | SLA Status | Priority | Source Selecting any combination must dynamically update all relevant KPIs, visuals and pages. Example: 2026 + July + Project X + Riyadh should update Requisitions, Openings, Joined, Remaining, Pipeline, SLA, Aging, Recruiter/HM Performance, Offers, Actions and Quality. Required: * Synced slicers * Cross-filtering * Drill-down * Drill-through * Dynamic titles * Tooltips * Searchable filters * Reset Filters * Detailed record views 12. Executive TA Dashboard A professional executive page should summarize: * Total Recruitment Demand * Joined * Under Joining * Remaining * Completion % * Open Requisitions * Critical Vacancies * SLA Compliance/Breaches * Aging * Offer Acceptance * Pipeline * Monthly Hiring Trend * Major Bottlenecks * Recruiter Performance * HM Delays * Project/Location Performance * Key Risks & Required Actions Executives should understand overall TA performance within seconds and drill into details when required. 13. Data Entry & Automation Manual data entry must be minimized. Recruitment users should maintain transactional information only: Requisition → Candidate → Stage → Dates → Status → Feedback → Offer → Acceptance → Joining Power BI should automatically calculate KPIs such as: Remaining, Completion %, Aging, SLA, Time to Fill, Time to Offer, Time to Join, Conversion, Productivity, HM Delay, Trends, Risks and Data Quality. Recruiters should not manually calculate KPIs. 14. Data Assessment & Data Model – Critical Requirement Before building visuals, the freelancer must review our available recruitment data and recommend the correct structure. The first stage should be: Data Assessment → Required Fields/Data Dictionary → Data Structure → Data Model → KPI Logic → Dashboard Development The freelancer should define: * Required tables and fields * Unique IDs * Mandatory fields * Requisition structure * Candidate pipeline structure * Interview data * Offer/Joining data * SLA structure * Action ownership * Data validation rules * Data-entry requirements If additional Excel/SharePoint input templates are needed, they should be designed as part of the solution. The model should use professional practices including: Star Schema, Power Query, Advanced DAX, Calendar/Date Dimension, proper relationships, KPI measures and performance optimization. Multiple recruitment dates (Req Creation, Approval, CV, Interview, Offer, Acceptance, Expected Joining, Actual Joining, Closure) must be modeled correctly. The architecture should also allow future integration with an ATS/HR system without rebuilding the dashboard. 15. Data Accuracy Dashboard numbers must reconcile with source data. Special attention is required to avoid: * Duplicate Requisitions * Duplicate Candidates * Incorrect Opening Counts * Incorrect Joined/Remaining * Many-to-many relationship issues * Incorrect filter context Accuracy and reconciliation are mandatory. Deliverables * Data Assessment * Data Dictionary / Required Fields * Recommended Data Entry Structure * Power BI Data Model * Complete PBIX * Power Query & DAX * Recruitment Overview * Demand vs Delivery * Pipeline/Funnel * SLA & Aging * Daily Action Center * Recruiter Performance * Hiring Manager Performance * Offer & Joining * Source Performance * Project/Location Analysis * Critical Vacancies/Risk * Data Health * Executive TA Dashboard * Global Filters & Drill-through * Data Validation * KPI Definitions * User Guide * Knowledge Transfer Freelancer Requirements Strong experience required in: Power BI | Advanced DAX | Power Query | Data Modeling | HR/Recruitment Analytics | KPI Development | Executive Dashboards Previous Talent Acquisition / Recruitment Analytics experience is highly preferred. Please provide: * Similar Power BI examples/screenshots * HR/Recruitment dashboard examples * Proposed approach * Proposed data model * Timeline * Fixed project cost * Revisions included * Support period Generic proposals will not be considered. The final solution should provide a single source of truth for the complete Talent Acquisition operation, from daily operational management to executive-level reporting.

Skills required