Database Administrator
Accountable for database integrity, performance and access control.
3tasks in this job
21skills it uses
6tools named
The skills this job leans on most
- 1Enforcing and auditing data accessNeeded in 3 of 3 tasks
- 2Diagnosing and remedying query and database performanceNeeded in 2 of 3 tasks
- 3Identifying keys and testing referential integrityNeeded in 2 of 3 tasks
- 4Applying data classification and handling rulesNeeded in 2 of 3 tasks
- 5Diagnosing incorrect query and calculation resultsCore to this role
ToolsMicrosoft SQL Server (with SSMS)PostgreSQLOracle DatabaseGrafanaDynatraceSQL (query language)Git / GitHubMicrosoft ExcelPythonSQL Server Reporting Services (SSRS)Azure SQL Database
All 3 tasks, where people get stuck and all 21 skills
Tasks
- Diagnose a database integrity or performance problem and verify the correction
- Triage a suspected data security or personal data breach and preserve evidence
- Apply an approved data access grant or revocation and prove its effect
Where people get stuck
All skills
- Applying data classification and handling rules
- Enforcing and auditing data access
- Identifying keys and testing referential integrity
- Assigning and operating data ownership and stewardship
- Designing role-based access entitlement models
- Escalating unresolved risks with evidence and clear ownership
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Monitoring and testing data control effectiveness
- Monitoring data quality and freshness in production
- Preparing change records with impact assessment and rollback
- Preserving incident evidence and timeline
- 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
- Repairing data defects reversibly under owner authority
- Running incident command: severity, timeline and status updates
- Testing changes to data services and business systems for business meaning and downstream impact
- Tracing data lineage upstream and downstream
- Writing verifiable requirements and acceptance criteria
Paths to start
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
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
Privacy, Security and Access for Data and AI
Protect personal data and access with impact assessments and incident evidence.
- Modules
- 5 open
- Practice data
- Raket Parts
5tasks in this job
45skills it uses
11tools named
The skills this job leans on most
- 1Identifying keys and testing referential integrityNeeded in 4 of 5 tasks
- 2Enforcing and auditing data accessNeeded in 4 of 5 tasks
- 3Diagnosing and remedying query and database performanceNeeded in 3 of 5 tasks
- 4Applying data classification and handling rulesNeeded in 2 of 5 tasks
- 5Diagnosing incorrect query and calculation resultsCore to this role
ToolsMicrosoft SQL Server (with SSMS)PostgreSQLOracle DatabaseGrafanaDynatraceSQL (query language)+ 5 more
All 5 tasks, where people get stuck and all 45 skills
Tasks
- Diagnose a database integrity or performance problem and verify the correction
- Triage a suspected data security or personal data breach and preserve evidence
- Prepare and verify a data-service release or migration for change approval
- Apply an approved data access grant or revocation and prove its effect
- Automate a recurring reporting or data task with controls and a named owner
Where people get stuck
- Gating releases on evidence with rollback ready
- Planning and validating controlled data migrations
- Escalating unresolved risks with evidence and clear ownership
All skills
- Applying data classification and handling rules
- Diagnosing and remedying query and database performance
- Enforcing and auditing data access
- Identifying keys and testing referential integrity
- Assessing change risk, collisions and go or no-go
- Assessing data-service continuity and recoverability
- 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
- Building decision-focused reports and dashboards
- Coordinating accountable handoffs between teams
- Debugging data and application services from evidence
- Designing automated pipelines and processes that fail safely and recover
- Designing enforceable data governance policies
- Designing relational schemas: keys, constraints and normalisation
- Designing role-based access entitlement models
- Designing semantic models for governed analytics
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Explaining technical work to accountable non-specialists
- Facilitating evidence-led retrospectives and corrective actions
- Gating releases on evidence with rollback ready
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Mapping proposed process changes and control impacts
- Monitoring and testing data control effectiveness
- Monitoring data quality and freshness in production
- Planning and validating controlled data migrations
- Preparing change records with impact assessment and rollback
- Preserving incident evidence and timeline
- Rating risks against appetite and choosing proportionate treatment
- Reading and tracing unfamiliar code
- 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
- Repairing data defects reversibly under owner authority
- Reviewing human- and AI-generated code changes for correctness and risk
- Running incident command: severity, timeline and status updates
- Standardising and cleaning data under agreed rules
- Testing changes to data services and business systems for business meaning and downstream impact
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Writing maintainable code for analytical and data work
- Writing verifiable requirements and acceptance criteria
Paths to start
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
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
9tasks in this job
80skills it uses
10tools named
The skills this job leans on most
- 1Enforcing and auditing data accessNeeded in 6 of 9 tasks
- 2Gating releases on evidence with rollback readyNeeded in 5 of 9 tasks
- 3Identifying keys and testing referential integrityNeeded in 5 of 9 tasks
- 4Diagnosing and remedying query and database performanceNeeded in 4 of 9 tasks
- 5Diagnosing incorrect query and calculation resultsCore to this role
ToolsMicrosoft SQL Server (with SSMS)Oracle DatabasePostgreSQLSQL (query language)ServiceNowGit / GitHub+ 4 more
All 9 tasks, where people get stuck and all 80 skills
Tasks
- Diagnose a database integrity or performance problem and verify the correction
- Triage a suspected data security or personal data breach and preserve evidence
- Prepare and verify a data-service release or migration for change approval
- Lead an incident through containment, restoration and communication
- Apply an approved data access grant or revocation and prove its effect
- Automate a recurring reporting or data task with controls and a named owner
- Design and review governed data-access entitlement policy
- Plan and demonstrate controlled data-service restoration
- Test the design and operating effectiveness of a data-dependent control
Where people get stuck
- Gating releases on evidence with rollback ready
- Escalating unresolved risks with evidence and clear ownership
- Assessing change risk, collisions and go or no-go
All skills
- Diagnosing and remedying query and database performance
- Enforcing and auditing data access
- Gating releases on evidence with rollback ready
- Identifying keys and testing referential integrity
- Analysing error patterns and failure modes in models and AI systems
- Applying data classification and handling rules
- Assessing change risk, collisions and go or no-go
- Assessing data-service continuity and recoverability
- 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
- Building decision-focused reports and dashboards
- Classifying AI uses against regulatory obligations
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Constructing clear and honest charts
- Controlling disclosure risk in shared data and outputs
- Coordinating accountable handoffs between teams
- Debugging data and application services from evidence
- Designing automated pipelines and processes that fail safely and recover
- Designing enforceable data governance policies
- Designing relational schemas: keys, constraints and normalisation
- Designing role-based access entitlement models
- Designing semantic models for governed analytics
- Designing testable data controls
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating service performance and quality trade-offs
- Evaluating software architecture for data and AI systems
- Explaining control types, dependencies and compensating controls
- Explaining technical work to accountable non-specialists
- Facilitating evidence-led retrospectives and corrective actions
- Giving specific developmental feedback on data and AI work
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether uncertainty changes the decision
- Locating and acting on personal data for individual rights requests
- Mapping personal data processing and flows
- Mapping proposed process changes and control impacts
- Monitoring and testing data control effectiveness
- Monitoring data quality and freshness in production
- Planning and validating controlled data migrations
- Preparing change records with impact assessment and rollback
- Presenting and defending evidence-based recommendations to decision-makers
- Preserving incident evidence and timeline
- Rating risks against appetite and choosing proportionate treatment
- Reading and tracing unfamiliar code
- Reading charts and dashboards correctly, including their state
- Recognising and containing suspected personal data breaches
- Recognising and resolving ethical conflicts in data and AI work
- Recognising cybersecurity threats to data work
- Recognising misleading numerical claims
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Repairing data defects reversibly under owner authority
- Resolving consent and suppression status across systems
- Reviewing human- and AI-generated code changes for correctness and risk
- Running incident command: severity, timeline and status updates
- Sampling and reviewing a team's work against standards
- Selecting charts for evidence and decisions
- Setting and reviewing reliability objectives and error budgets for data and AI services
- Standardising and cleaning data under agreed rules
- Testing changes to data services and business systems for business meaning and downstream impact
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Writing data quality rules
- Writing evidence-led findings and auditable recommendations with their limits
- Writing maintainable code for analytical and data work
- Writing verifiable requirements and acceptance criteria
All tools
- Microsoft SQL Server (with SSMS)
- Oracle Database
- PostgreSQL
- SQL (query language)
- ServiceNow
- Git / GitHub
- Microsoft Excel
- Python
- SQL Server Reporting Services (SSRS)
- Azure SQL Database
Paths to start
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
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
Coming soonData Product Reliability: Release Gates, Service Levels and Incidents
About the role
Accountable for database integrity, performance and access control. Implements entitlement policy in the database and proves that revoked access is gone. Differs from the Data Governance Lead because the Database Administrator implements access policy rather than setting it.
Also called DBA