People Operations Lead
Accountable for joiner, mover and leaver processes, HR system rules and the quality of the records and payroll inputs they produce.
3tasks in this job
24skills it uses
7tools named
The skills this job leans on most
- 1Diagnosing data quality exceptionsNeeded in 1 of 3 tasks
- 2Writing data quality rulesNeeded in 1 of 3 tasks
- 3Repairing data defects reversibly under owner authorityNeeded in 1 of 3 tasks
- 4Enforcing and auditing data accessNeeded in 1 of 3 tasks
- 5Applying data classification and handling rulesNeeded in 1 of 3 tasks
ToolsVisma payroll (Visma Lønn, Visma Enterprise HRM, Visma Løn)iTrentWorkdayHiBob (Bob)Sympa HRMicrosoft ExcelServiceNow HR Service Delivery
All 3 tasks, where people get stuck and all 24 skills
Tasks
- Run a controlled payroll calculation and payment readiness check
- Govern employment joiner, mover and leaver changes
- Monitor and correct data quality in a domain or system of record and drive remediation at source
Where people get stuck
- Testing changes to data services and business systems for business meaning and downstream impact
- Reconciling finance subledgers and close records
- Recalculating pay and incentive outcomes from plan rules
All skills
- Applying data classification and handling rules
- Diagnosing data quality exceptions
- Enforcing and auditing data access
- Repairing data defects reversibly under owner authority
- Writing data quality rules
- Applying effective dating and retroactive change rules to records
- Assessing data source credibility and fitness for a question
- Assigning and operating data ownership and stewardship
- Designing and validating digital analytics event measurement
- Designing efficient and reproducible investigations
- Diagnosing duplicate records
- Diagnosing operational handoffs and flow
- Escalating unresolved risks with evidence and clear ownership
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Profiling data
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
Paths to start
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
7tasks in this job
59skills it uses
8tools named
The skills this job leans on most
- 1Enforcing and auditing data accessNeeded in 4 of 7 tasks
- 2Diagnosing data quality exceptionsNeeded in 2 of 7 tasks
- 3Repairing data defects reversibly under owner authorityNeeded in 2 of 7 tasks
- 4Writing data quality rulesNeeded in 1 of 7 tasks
- 5Testing changes to data services and business systems for business meaning and downstream impactNeeded in 1 of 7 tasks
ToolsVisma payroll (Visma Lønn, Visma Enterprise HRM, Visma Løn)iTrentWorkdayHiBob (Bob)Sympa HRMicrosoft Excel+ 2 more
All 7 tasks, where people get stuck and all 59 skills
Tasks
- Run a controlled payroll calculation and payment readiness check
- Investigate and resolve an individual payroll exception
- Govern employment joiner, mover and leaver changes
- Apply an approved data access grant or revocation and prove its effect
- Test the design and operating effectiveness of a data-dependent control
- Monitor and correct data quality in a domain or system of record and drive remediation at source
- Configure, test and release a change to a business system of record under change control
Where people get stuck
- Assigning and operating data ownership and stewardship
- Designing enforceable data governance policies
- Identifying and prioritising critical data elements
All skills
- Diagnosing data quality exceptions
- Enforcing and auditing data access
- Repairing data defects reversibly under owner authority
- Testing changes to data services and business systems for business meaning and downstream impact
- Writing data quality rules
- Applying data classification and handling rules
- Applying effective dating and retroactive change rules to records
- Assessing data source credibility and fitness for a question
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assigning and operating data ownership and stewardship
- Building data protection by design into data products and pipelines
- Calculating and verifying KPIs against their specification
- Combining tables safely: cardinality, fan-out and conservation of totals
- Comparing periods consistently
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing efficient and reproducible investigations
- Designing enforceable data governance policies
- Designing role-based access entitlement models
- Diagnosing duplicate records
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Facilitating evidence-led retrospectives and corrective actions
- Gating releases on evidence with rollback ready
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Influencing change without formal authority
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Managing master data identities and exceptions
- Monitoring and testing data control effectiveness
- Monitoring data quality and freshness in production
- Preparing change records with impact assessment and rollback
- Profiling data
- Reading business metrics
- Reading data tables: rows, fields, types and units
- Recalculating pay and incentive outcomes from plan rules
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Reconciling finance subledgers and close records
- Resolving and escalating pay, incentive and payment exceptions within authority
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Working through stakeholder conflict over evidence and responsibility
- Writing verifiable requirements and acceptance criteria
All tools
- Visma payroll (Visma Lønn, Visma Enterprise HRM, Visma Løn)
- iTrent
- Workday
- HiBob (Bob)
- Sympa HR
- Microsoft Excel
- Microsoft Power BI
- ServiceNow HR Service Delivery
Paths to start
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
7tasks in this job
72skills it uses
9tools named
The skills this job leans on most
- 1Diagnosing data quality exceptionsNeeded in 4 of 7 tasks
- 2Repairing data defects reversibly under owner authorityNeeded in 4 of 7 tasks
- 3Enforcing and auditing data accessNeeded in 4 of 7 tasks
- 4Writing data quality rulesNeeded in 2 of 7 tasks
- 5Testing changes to data services and business systems for business meaning and downstream impactNeeded in 1 of 7 tasks
ToolsMicrosoft ExcelSAP S/4HANAVisma payroll (Visma Lønn, Visma Enterprise HRM, Visma Løn)iTrentWorkdayHiBob (Bob)+ 3 more
All 7 tasks, where people get stuck and all 72 skills
Tasks
- Reconcile payroll to finance postings
- Run a controlled payroll calculation and payment readiness check
- Govern employment joiner, mover and leaver changes
- Assign data ownership and stewardship and decide a domain's data standards
- Monitor and correct data quality in a domain or system of record and drive remediation at source
- Design data-dependent controls for a new or changed finance or people process, system or automation
- Configure, test and release a change to a business system of record under change control
Where people get stuck
All skills
- Diagnosing data quality exceptions
- Enforcing and auditing data access
- Repairing data defects reversibly under owner authority
- Testing changes to data services and business systems for business meaning and downstream impact
- Writing data quality rules
- Applying data classification and handling rules
- Applying effective dating and retroactive change rules to records
- Assessing data source credibility and fitness for a question
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assessing privacy risk through data protection impact assessments
- Assigning and operating data ownership and stewardship
- Building data protection by design into data products and pipelines
- Calculating and verifying KPIs against their specification
- Classifying AI uses against regulatory obligations
- Combining tables safely: cardinality, fan-out and conservation of totals
- Comparing periods consistently
- Controlling disclosure risk in shared data and outputs
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing decision rights and dispute routes for data and AI work
- Designing efficient and reproducible investigations
- Designing enforceable data governance policies
- Designing role-based access entitlement models
- Designing testable data controls
- Diagnosing duplicate records
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Facilitating evidence-led retrospectives and corrective actions
- Gating releases on evidence with rollback ready
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and prioritising critical data elements
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Influencing change without formal authority
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether and how to use AI for a task
- Locating and acting on personal data for individual rights requests
- Managing master data identities and exceptions
- Mapping personal data processing and flows
- Mapping stakeholders' decisions, constraints and needs
- Monitoring and testing data control effectiveness
- Monitoring data quality and freshness in production
- Preparing change records with impact assessment and rollback
- Profiling data
- Reading business metrics
- Reading data tables: rows, fields, types and units
- Recalculating pay and incentive outcomes from plan rules
- Recognising and containing suspected personal data breaches
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Reconciling finance subledgers and close records
- Resolving and escalating pay, incentive and payment exceptions within authority
- Resolving consent and suppression status across systems
- Sampling and reviewing a team's work against standards
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Working through stakeholder conflict over evidence and responsibility
- Writing verifiable requirements and acceptance criteria
All tools
- Microsoft Excel
- SAP S/4HANA
- Visma payroll (Visma Lønn, Visma Enterprise HRM, Visma Løn)
- iTrent
- Workday
- HiBob (Bob)
- Sympa HR
- Microsoft Power BI
- ServiceNow
Paths to start
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
About the role
Accountable for joiner, mover and leaver processes, HR system rules and the quality of the records and payroll inputs they produce. Leads the work and reviews others' changes without line management. Data judgement sits in HR data quality and the controls that protect pay and personal data.
Also called HR Operations Lead