About the role
Responsibilities:
- Build the Full Talent Picture web portal employee profiles with 8 data tabs (onboarding, goals, performance, competencies, learning & development, succession, career history, and restricted HR notes) plus an AI-generated overview and aggregated dashboards for L& D and organizational development insights.
- Develop automated scoring engines for goal quality score, mid-year signal score, and manager feedback quality score, including text-analysis components that classify free-text manager feedback against defined keyword families, weights, and thresholds.
- Build data integration pipelines scheduled, validated feeds from Workday (HCM), the L& D portal, competency assessment data, internal dashboards, and Excel trackers into a single employee data store, eliminating manual reconciliation.
- Implement role-based access control enforced, with field-level visibility rules across reporting managers, HRBPs, and senior leaders, with sensitive fields locked (frosted-panel pattern) rather than hidden.
- Develop intelligence features for performance evaluation (PE) trends and career velocity metrics, attrition risk indicators, auto-generated prioritization lists, and a correlation tracker that flags mid-year vs. final-rating divergence for HRBP investigation.
- Deploy, test, and support write-tested, documented, reviewable code under Tech Strategy Team governance; deploy to internal infrastructure; support a single-function pilot; and iterate to enterprise rollout.
Requirements:
- 3-6 years of full-stack software engineering experience building and shipping production web applications.
- Front end: strong proficiency in a modern JavaScript framework (React/Angular/Vue) with responsive, data-dense dashboard/UI development and a charting library (Chart.js/D3/Highcharts).
- Back end and APIs: Python (Django/FastAPI) or Node.js; REST API design; authentication and authorization (RBAC) implementation.
- Data: strong SQL and data modeling; experience building ETL/integration pipelines from heterogeneous sources (databases, spreadsheets, enterprise systems).
- Engineering discipline: Git-based workflows, code reviews, unit/integration testing, and maintainable, well-documented code.
- Confidentiality: proven judgment in handling sensitive personal data (HR/performance data) with strict confidentiality and security awareness.