Role-specific skills and tools
- Excel or Google Sheets
- SQL and relational data concepts
- Looker Studio, Power BI, Tableau, or similar BI tools
- Analytics and source-system integrations
- Data-quality validation
- Clear analytical communication
Data & Analytics
Hire LATAM Data and Analytics Talent
Turn operational and customer data into reliable reporting with professionals evaluated for your sources, definitions, tools, and decision-making needs.
Role overview
Build the role around the work
Data roles range from recurring reporting and dashboard ownership to analytics engineering and deeper statistical work. The title alone does not define the required technical depth.
Outland.Work helps clients identify the decisions the work must support, then evaluate data fluency, source-system experience, analytical reasoning, documentation, and communication.
Typical responsibilities
- Recurring business and performance reporting
- Dashboard creation and maintenance
- Data cleaning and quality checks
- SQL queries and exploratory analysis
- Metric definitions and documentation
- Stakeholder-ready findings and recommendations
How Outland evaluates the fit
- Relevant analysis or dashboard examples
- Reasoning through a business question
- SQL, spreadsheet, or BI exercise appropriate to the role
- Data-quality and validation approach
- Ability to explain findings to non-technical stakeholders
Collaboration
U.S. workday overlap
Agree on metric definitions, source ownership, refresh schedules, access controls, and review windows. Sensitive customer, employee, and financial data should be limited to what the role requires.
Engagement
Direct or managed support
Use the client marketplace to review talent and manage the hiring decision directly, or discuss Outland-managed support when you want help defining the role, coordinating onboarding, and maintaining continuity.
Review current pricing and plansMatching
From brief to interview
Bring the business questions, source systems, current reports, preferred tools, refresh cadence, and known data-quality issues. That makes the interview about your real analytics environment.
See how hiring worksUseful hiring guides
Frequently asked questions
Do I need a data analyst or data engineer?
Choose an analyst for reporting, dashboards, business questions, and interpretation. Choose an engineer when the primary need is building and maintaining pipelines, models, or data infrastructure. Some scopes need both.
How can I evaluate analytics work?
Use a representative dataset or reporting problem, ask the candidate to identify data-quality risks, and evaluate both the analysis and the clarity of the explanation.
How should sensitive data be protected?
Limit access by source and role, use approved systems, remove unnecessary personal information, document exports, and define how working files must be retained or deleted.