Data Analyst Job Description Template
Use this ready-to-customize data analyst job description template to define the role clearly, attract relevant candidates, and screen applicants against consistent criteria.
Role overview
A Data Analyst collects, cleans, analyses, and visualises data to support business decisions. The role requires analytical thinking, SQL or spreadsheet capability, comfort with dashboards, and the ability to translate data into clear recommendations.
What they own
- Collect, clean, validate, and analyse data from multiple business systems.
- Write SQL queries or use analytics tools to extract and transform data.
- Build dashboards, reports, and recurring performance trackers.
- Analyse trends, cohorts, funnels, operations, revenue, product usage, or customer behaviour.
- Work with business teams to define metrics and answer decision questions.
- Present findings clearly with context, caveats, and recommendations.
- Improve data quality, documentation, and reporting processes over time.
Required skills & qualifications
- Strong analytical and problem-solving skills.
- Working knowledge of SQL, Excel/Google Sheets, and at least one BI or visualization tool.
- Ability to clean, structure, and interpret data accurately.
- Comfort communicating insights to non-technical stakeholders.
- Attention to detail and ability to validate assumptions before sharing results.
Preferred qualifications
- Experience with Python, R, dbt, BigQuery, Snowflake, Tableau, Power BI, Looker, or Metabase.
- Experience with product analytics, marketing analytics, financial analytics, or operations analytics.
- Ability to design metrics, build dashboards, and automate recurring reports.
- Exposure to statistical analysis, experimentation, or forecasting.
Suggested screening rubric
Use this rubric as a first-pass evaluation structure for data analyst candidates. Adjust the weightings based on seniority, company stage, and role expectations.
| Criterion | Suggested weight | What to look for |
|---|---|---|
| Analytical toolkit | 30% | SQL, spreadsheets, BI tools, data cleaning, visualization, and analytics workflows. |
| Business impact | 25% | Evidence that analysis influenced decisions, revenue, efficiency, product changes, or operations. |
| Data quality and rigor | 20% | Validation, documentation, metric definitions, and ability to handle messy data. |
| Communication | 15% | Clear dashboards, stakeholder presentations, and decision-oriented storytelling. |
| Domain fit | 10% | Industry, function, data stack, and company-stage relevance. |
Interview handoff questions
Once candidates are shortlisted, hiring managers can use these questions to validate resume claims and assess role fit.
- 01Tell me about an analysis that changed a business decision.
- 02How do you validate whether a dashboard number is correct?
- 03What metrics would you track for a new product feature?
- 04How do you handle missing or inconsistent data?
- 05Explain a complex analysis to a non-technical stakeholder.
Resume screening red flags
- Resume lists tools but does not show business outcomes or decision impact.
- No evidence of SQL, data cleaning, or dashboard ownership where those are required.
- Overly academic analysis with weak business communication.
- No mention of validation, data quality, or metric definitions.
How HireSort helps with this role
- Turn the job description into a structured screening rubric.
- Upload resumes in bulk and parse key candidate information automatically.
- Score every candidate against the same role-specific criteria.
- Review ranked shortlists with evidence, strengths, and missing elements.
- Store candidates in a reusable resume repository for future roles.
- Track candidate stages from New to Shortlisted, Interviews, Offer, Hired, Rejected, or On Hold.
Ready to hire a Data Analyst?
Use HireSort to generate a structured JD, screen resumes faster, and identify the most relevant data analyst candidates with explainable AI scoring.
Frequently asked questions
It should include a clear role overview, responsibilities, required skills, preferred qualifications, success expectations, and the screening criteria your team will use to evaluate candidates.