Turn raw data into decisions that leadership acts on.
Data analyst resume example with SQL, dashboard, and insight bullets. Shows hiring managers you can go from messy dataset to clear recommendation. Free on LumiCV.
Automated 14 weekly reports (SQL + Python + Tableau) previously taking 3 analysts 6 hours each, freeing the team to focus on strategic work while eliminating report-delivery errors.
Identified $340K in duplicate vendor payments by joining 3 internal datasets with Python, triggering an audit that recovered funds and closed the process gap within 60 days.
Built self-serve dashboard (Looker + BigQuery) used by 120 sales reps daily to prioritise outreach - adoption replaced 80% of ad-hoc analyst requests within 6 weeks of launch.
Each bullet: strong verb → specific action → quantified result. Copy the structure, not the words.
Automated 14 weekly reports (SQL + Python + Tableau) previously taking 3 analysts 6 hours each, freeing the team to focus on strategic work while eliminating report-delivery errors.
Identified $340K in duplicate vendor payments by joining 3 internal datasets with Python, triggering an audit that recovered funds and closed the process gap within 60 days.
Built self-serve dashboard (Looker + BigQuery) used by 120 sales reps daily to prioritise outreach - adoption replaced 80% of ad-hoc analyst requests within 6 weeks of launch.
How LumiCV helps: Paste any job description and our AI rewrites your bullets to match the role's exact keywords. Every template is ATS-parseable out of the box.
These terms appear most frequently in Data Analyst job descriptions. Missing them means your resume won't surface.
Data analyst resumes succeed when they bridge technical credibility with business influence. Anyone can write SQL - the candidates who stand out are those who connected the query to a decision that saved money, grew revenue, or reduced a business risk.
Frame each bullet as: data source + analysis method + decision made + outcome. Avoid passive language like 'was responsible for reporting.' Use active verbs: 'built', 'automated', 'identified', 'recommended', 'presented'.
ATS checklist: SQL (PostgreSQL, BigQuery, Snowflake), BI tools (Tableau, Looker, Power BI, Metabase), Python or R for statistical work, Excel/Sheets for ad-hoc analysis, and data pipeline basics (dbt, Airflow). For product analytics roles, add Mixpanel, Amplitude, or PostHog.
A strong Data Analyst resume should include: a concise professional summary, quantified experience bullets showing impact, a skills section with relevant keywords, and clean ATS-parseable formatting. See the example bullets above for the level of specificity hiring managers expect.
Use a single-column or ATS-safe two-column template, include role-specific keywords naturally in your bullets, avoid tables and text boxes, and export as a real-text PDF (not an image). LumiCV's templates are parse-tested: each is rendered to PDF and verified with a machine parser to recover every field in the correct reading order.
Key ATS keywords for a Data Analyst resume include: SQL, Python, Tableau, Power BI, Looker, Excel, BigQuery, Snowflake, dbt, data visualisation, statistics, stakeholder management. Use these naturally throughout your experience bullets and skills section - keyword stuffing in a hidden section will not work on modern ATS systems.
For most Data Analyst roles, one page is ideal for under 7 years of experience. Two pages are appropriate for senior roles with 10+ years. Beyond two pages is rarely justified. Cut anything that doesn't directly support why you're qualified for the role you're targeting.
Yes. LumiCV's free plan includes all 11 country formats and 3 ATS templates and lets you export your resume as a PDF. Pro (from $8.25/month billed yearly) adds 14 more templates and unlimited AI tailoring - paste a job description and LumiCV rewrites your bullets to match the role's keywords.
The analyst cover letter that shows business sense, not just SQL fluency.
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