Data Analyst CV Template
Data Analysts transform raw data into actionable insights that drive business decisions. UK employers look for analysts who combine strong technical skills in SQL and Python with the ability to communicate findings clearly to non-technical stakeholders. A compelling CV showcases your analytical toolkit alongside real examples of how your insights influenced strategy.
What recruiters look for in a Data Analyst CV
- Proficiency in SQL and at least one programming language (Python or R)
- Experience with BI tools like Tableau, Power BI, or Looker
- Examples of translating data into business recommendations with measurable outcomes
- Ability to communicate complex findings to non-technical audiences
- Familiarity with data governance, quality assurance, and GDPR compliance
- Evidence of proactive analysis — finding insights without being asked
Key skills for a Data Analyst CV
Example experience bullets for a Data Analyst
Use these as inspiration — always tailor bullets to your own experience and achievements.
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Tailor my CV nowFrequently asked questions
Do I need a degree to become a Data Analyst in the UK?
While many Data Analyst roles list a degree in a quantitative field, it's not always essential. Employers increasingly value practical skills and certifications (Google Data Analytics, Microsoft Power BI) alongside a portfolio of projects. Highlight relevant coursework, bootcamps, or self-taught skills prominently on your CV.
How should I present technical skills on a Data Analyst CV?
Create a dedicated 'Technical Skills' section near the top, grouping tools by category (e.g., Languages: SQL, Python; Visualisation: Tableau, Power BI; Databases: PostgreSQL, BigQuery). Then reinforce these skills in your experience bullets by showing how you used them to deliver results.
Should I include a portfolio link on my Data Analyst CV?
Absolutely. Link to a personal website or GitHub with 3-5 polished projects that demonstrate your analytical process — from data cleaning through to visualisation and insights. Kaggle competition entries also work well. Make sure each project has a clear business question and conclusion.