Find Data Analysts

About the profession

Data analysts answer business questions with evidence: what changed, for whom, and whether it was the thing you did. The job is equal parts SQL, modelling and communication — an analysis nobody acts on has no value.

The best predictor of fit is whether the analyst asks about the decision before writing a query. Domain familiarity matters too: e-commerce, SaaS, finance and marketing analytics have different core metrics.

Skills to look for

• Advanced SQL
• Data modelling and warehouse structure
• BI tools (Looker, Power BI, Tableau, Metabase)
• Python or R for analysis
• Spreadsheet modelling
• Experiment design and A/B testing
• Product and marketing analytics
• Clear written reporting

Common specialties

Product analytics

Funnels, retention and feature adoption.

Marketing analytics

Attribution, channel performance and spend efficiency.

Financial analysis

Revenue, margin and forecasting models.

Analytics engineering

dbt models and a trustworthy semantic layer.

Operations analytics

Supply, logistics and capacity reporting.

Experience and seniority

Junior analysts answer defined questions and maintain dashboards. Mid-level analysts choose the method and own a domain. Senior analysts shape which questions get asked, build the metric definitions and push back on bad ones.

Remote, hybrid or on-site

Remote-friendly wherever data access allows it. Hybrid is common because analysts benefit from being close to the teams making decisions.

How unigrig matching works for this role

Say which decisions the role supports and what data already exists. unigrig matches on tooling, seniority and industry experience taken from the professional's own profile.