Explore Tasks
Automate a recurring reporting or data task with controls and a named owner
A team receives an automated recurring task (report, reconciliation, extract) with tests, failure alerts and an owner.
22jobs do it
2jobs help with it
32skills it needs
- Data Analyst
- BI Developer
- Database Administrator
- Accounts Payable Specialist
- Management Accountant
- FP&A Analyst
- Procurement Specialist
- Management Accounting Lead
- FP&A Lead
- Finance Business Partner
- Category Lead
- People Analyst
- Sales Operations Analyst
- Revenue Operations Lead
- Operations Analyst
- Project Coordinator
- PMO Manager
- Finance Systems Analyst
- Credit Manager
- HRIS Analyst
- Reward Manager
- Workforce Planning Manager
- Revenue Operations Manager
- Operations Manager
Does itHelps with it
- Reading and tracing unfamiliar code
- Reviewing human- and AI-generated code changes for correctness and risk
- Sampling and reviewing a team's work against standards
- Diagnosing misleading data visualisations
- Verifying reports and dashboards before and after release
- Verifying AI-assisted outputs against sources
- Disclosing AI contribution to professional work
- Testing competing explanations with discriminating evidence
- Independently checking analytical conclusions and claims
- Escalating unresolved risks with evidence and clear ownership
- Giving specific developmental feedback on data and AI work
- Judging the materiality of defects and deficiencies for the intended use
- Writing maintainable code for analytical and data work
- Gating releases on evidence with rollback ready
- Designing automated pipelines and processes that fail safely and recover
- Establishing and declaring data grain
- Standardising and cleaning data under agreed rules
- Tracing data lineage upstream and downstream
- Monitoring data quality and freshness in production
- Building decision-focused reports and dashboards
- Designing semantic models for governed analytics
- Identifying keys and testing referential integrity
- Designing relational schemas: keys, constraints and normalisation
- Designing dimensional models with explicit grain
- Testing changes to data services and business systems for business meaning and downstream impact
- Designing and validating batch and streaming ingestion
- Engineering production data transformations
- Recovering data pipelines safely
- Building data protection by design into data products and pipelines
- Writing evidence-led findings and auditable recommendations with their limits
- Making accountable decisions under uncertainty
- Interpreting policy scope and delegated authority limits
Paths that teach the skills it needs
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
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 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
Coming soonAnalytics Engineering: Tested, Version-controlled Transformation