Senior HR Data Manager — Strategic HRIS & Reporting Lead

HR Data Manager — HRIS, Data Governance & Talent Metrics

The HR Data Manager sits at the intersection of human resources, data engineering, and business strategy. Responsible for managing HR information systems (HRIS), enforcing data governance, and translating raw personnel data into actionable talent metrics, this role ensures organizations make evidence-based decisions about hiring, retention, performance, and workforce planning.

Core responsibilities

1. HRIS administration: Configure, maintain, and optimize HR systems (e.g., Workday, SuccessFactors, BambooHR). Manage user access, integrations, system upgrades, and custom reporting.
2. Data governance: Define and enforce data standards, ownership, and lifecycle policies across employee records. Implement data quality checks, remediation workflows, and compliance controls for privacy and regulations (e.g., GDPR, CCPA where applicable).
3. People analytics & reporting: Develop dashboards and regular reports on headcount, turnover, time-to-hire, diversity metrics, compensation trends, and performance distributions. Translate findings into recommendations for HR business partners and leadership.
4. Workforce planning support: Provide scenario modeling and forecasting to support hiring plans, succession planning, and budget forecasting. Link talent metrics to financial and business KPIs.
5. Cross-functional collaboration: Partner with IT, finance, legal, and business leaders to ensure HR data needs are met and that integrations (payroll, benefits, ATS, LMS) are robust and secure.
6. Data security & compliance: Ensure HR data access follows least-privilege principles. Coordinate audits, maintain consent records, and support incident response for data breaches involving HR systems.
7. Process improvement & automation: Automate repetitive data tasks (e.g., onboarding data flows, batch updates) using APIs, ETL tools, or RPA; document processes and maintain runbooks.

Required skills & qualifications

• Technical: Proficiency with HRIS platforms, SQL, ETL tools, BI tools (e.g., Tableau, Power BI), and data modeling. Familiarity with APIs and identity/access management.
• Analytical: Strong statistical and analytical skills; ability to design meaningful KPIs and perform root-cause analysis.
• Governance & compliance: Experience implementing data governance frameworks and knowledge of relevant privacy laws.
• Interpersonal: Excellent communication to translate complex analytics for nontechnical stakeholders and to lead cross-functional initiatives.
• Education & experience: Typically a bachelor’s in HR, data science, IT, or related field; 5+ years in HRIS, HR analytics, or data management roles preferred.

Key metrics to track

• Time-to-hire, time-to-fill
• Voluntary and involuntary turnover rates
• Offer acceptance rate
• Internal mobility and succession bench strength
• Diversity & inclusion metrics by level and function
• HR data quality score (completeness, accuracy, timeliness)
• Cost-per-hire and recruitment source ROI

Best practices

• Establish clear data ownership: Assign stewards for each HR dataset with documented responsibilities.
• Standardize definitions: Create a metrics glossary so stakeholders use consistent definitions (e.g., “active headcount,” “new hire,” “terminated”).
• Automate validation: Implement automated data quality checks and alerts to catch anomalies early.
• Build self-service reporting: Empower HRBPs with curated dashboards and governed datasets to reduce ad-hoc requests.
• Prioritize privacy: Apply role-based access, anonymize datasets for analysis when possible, and keep retention schedules strict.

Typical challenges and solutions

• Fragmented systems: Use middleware or a centralized HR data warehouse to consolidate sources.
• Poor data quality: Run periodic audits, implement validation rules at capture points, and provide training for data owners.
• Stakeholder alignment: Run regular governance councils and circulate a roadmap showing impact of analytics work.
• Scaling analytics: Start with templated dashboards, then centralize complex models in a scalable BI layer.

Career path & advancement

An HR Data Manager can progress to Senior