Data Governance Lead
Accountable for data quality, access entitlement policy and permissible disclosure decisions for a data domain.
3tasks in this job
39skills it uses
8tools named
The skills this job leans on most
- 1Assessing lawful basis, purpose compatibility and minimisation for data reuseNeeded in 3 of 3 tasks
- 2Controlling disclosure risk in shared data and outputsNeeded in 1 of 3 tasks
- 3Interpreting policy scope and delegated authority limitsNeeded in 1 of 3 tasks
ToolsServiceNowCollibraMicrosoft PurviewOneTrustAtaccama ONEInformatica (IDMC, PowerCenter, Data Quality)SQL (query language)SAP Master Data Governance (MDG)
All 3 tasks, where people get stuck and all 39 skills
Tasks
- Review a proposed use, reuse, disclosure of or access to data and record the permitted-use decision
- Monitor and correct data quality in a domain or system of record and drive remediation at source
- Define master data match and survivorship rules and recommend golden-record changes for the data owner's approval
Where people get stuck
- Diagnosing duplicate records
- Enforcing and auditing data access
- Assigning and operating data ownership and stewardship
All skills
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Controlling disclosure risk in shared data and outputs
- Interpreting policy scope and delegated authority limits
- Applying data classification and handling rules
- Assessing data source credibility and fitness for a question
- 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
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing efficient and reproducible investigations
- Designing testable data controls
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing operational handoffs and flow
- Enforcing and auditing data access
- Escalating unresolved risks with evidence and clear ownership
- Facilitating evidence-led retrospectives and corrective actions
- Governing shared data definitions
- Influencing change without formal authority
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Locating and acting on personal data for individual rights requests
- Managing master data identities and exceptions
- Mapping personal data processing and flows
- Monitoring data quality and freshness in production
- Profiling data
- Recognising and containing suspected personal data breaches
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Resolving consent and suppression status across systems
- 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
- Working through stakeholder conflict over evidence and responsibility
- Writing data quality rules
Paths to start
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
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
Tool Path
SQL for Analysis
Answer real business questions with SQL, from your first query to finding why a number moved.
- Modules
- 5 open
- Runs in
- Your browser
6tasks in this job
54skills it uses
12tools named
The skills this job leans on most
- 1Assessing lawful basis, purpose compatibility and minimisation for data reuseNeeded in 6 of 6 tasks
- 2Assigning and operating data ownership and stewardshipNeeded in 5 of 6 tasks
- 3Diagnosing duplicate recordsNeeded in 4 of 6 tasks
- 4Enforcing and auditing data accessNeeded in 3 of 6 tasks
- 5Controlling disclosure risk in shared data and outputsNeeded in 3 of 6 tasks
ToolsSQL (query language)Informatica (IDMC, PowerCenter, Data Quality)ServiceNowCollibraOneTrustMicrosoft Purview+ 6 more
All 6 tasks, where people get stuck and all 54 skills
Tasks
- Assess data quality and fitness for a stated use
- Review a proposed use, reuse, disclosure of or access to data and record the permitted-use decision
- Design and review governed data-access entitlement policy
- 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
- Define master data match and survivorship rules and recommend golden-record changes for the data owner's approval
Where people get stuck
- Designing testable data controls
- Monitoring and testing data control effectiveness
- Testing the completeness and accuracy of reports and data that controls rely on
All skills
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assigning and operating data ownership and stewardship
- Controlling disclosure risk in shared data and outputs
- Diagnosing duplicate records
- Enforcing and auditing data access
- Applying data classification and handling rules
- Assessing data source credibility and fitness for a question
- Assessing privacy risk through data protection impact assessments
- Building data protection by design into data products and pipelines
- Classifying AI uses against regulatory obligations
- 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 data quality exceptions
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Facilitating evidence-led retrospectives and corrective actions
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and prioritising critical data elements
- 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
- Profiling data
- Recognising and containing suspected personal data breaches
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Resolving consent and suppression status across systems
- 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 data quality rules
All tools
- SQL (query language)
- Informatica (IDMC, PowerCenter, Data Quality)
- ServiceNow
- Collibra
- OneTrust
- Microsoft Purview
- Alation
- Microsoft SharePoint
- Ataccama ONE
- Microsoft Power BI
- Tableau
- SAP Master Data Governance (MDG)
Paths to start
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
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
Tool Path
SQL for Analysis
Answer real business questions with SQL, from your first query to finding why a number moved.
- Modules
- 5 open
- Runs in
- Your browser
7tasks in this job
61skills it uses
10tools named
The skills this job leans on most
- 1Assessing lawful basis, purpose compatibility and minimisation for data reuseNeeded in 6 of 7 tasks
- 2Designing testable data controlsNeeded in 5 of 7 tasks
- 3Controlling disclosure risk in shared data and outputsNeeded in 4 of 7 tasks
- 4Monitoring and testing data control effectivenessNeeded in 2 of 7 tasks
- 5Testing the completeness and accuracy of reports and data that controls rely onNeeded in 1 of 7 tasks
ToolsServiceNowCollibraOneTrustMicrosoft SharePointMicrosoft Power BISQL (query language)+ 4 more
All 7 tasks, where people get stuck and all 61 skills
Tasks
- Review a proposed use, reuse, disclosure of or access to data and record the permitted-use decision
- Evaluate an AI use case for suitability, value and risk before adoption
- Design and review governed data-access entitlement policy
- Assign data ownership and stewardship and decide a domain's data standards
- 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
- Define master data match and survivorship rules and recommend golden-record changes for the data owner's approval
Where people get stuck
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Interpreting policy scope and delegated authority limits
All skills
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Controlling disclosure risk in shared data and outputs
- Designing testable data controls
- Monitoring and testing data control effectiveness
- Testing the completeness and accuracy of reports and data that controls rely on
- Applying data classification and handling rules
- Assessing data source credibility and fitness for a question
- 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
- Classifying AI uses against regulatory obligations
- Designing and appraising samples
- Designing and running evaluations of AI systems
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing automated pipelines and processes that fail safely and recover
- 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
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Enforcing and auditing data access
- Escalating unresolved risks with evidence and clear ownership
- Explaining control types, dependencies and compensating controls
- Facilitating evidence-led retrospectives and corrective actions
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and prioritising critical data elements
- 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 proposed process changes and control impacts
- Mapping stakeholders' decisions, constraints and needs
- Monitoring data quality and freshness in production
- Profiling data
- Recognising and containing suspected personal data breaches
- Recognising cybersecurity threats to data work
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Resolving consent and suppression status across systems
- 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 data quality rules
All tools
- ServiceNow
- Collibra
- OneTrust
- Microsoft SharePoint
- Microsoft Power BI
- SQL (query language)
- Microsoft Purview
- Ataccama ONE
- Alation
- SAP Master Data Governance (MDG)
Paths to start
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
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
Tool Path
SQL for Analysis
Answer real business questions with SQL, from your first query to finding why a number moved.
- Modules
- 5 open
- Runs in
- Your browser
About the role
Accountable for data quality, access entitlement policy and permissible disclosure decisions for a data domain. Writes enforceable policy and decides who may use which data for what purpose. Owns these decisions, whereas the Data Protection Officer advises on and monitors their legal compliance independently.