Free Data Analyst Job Description Templates
Free data analyst job description templates: general, junior, senior, business operations, and marketing. Copy or download as DOCX in minutes.
Data Analyst Job Description Templates
5 free templates by type. Download as DOCX or copy-paste.
A data analyst is the person who turns the numbers your business already generates into decisions you can defend: which channel actually makes money, why customers leave, where the margin leaks. The five templates below give you a ready-to-use posting for the role, with the stack, work-sample, and remote fields built in. Fill in the brackets and post.
For a growing company, the first analytics hire is a turning point, because it usually means the founder is admitting the spreadsheets have outgrown one person's evenings. The posting for that hire has real work to do: name the questions, name the stack, and attract someone who can build a reporting foundation rather than just operate one.
At FirstHR, we build for small teams that hire without an HR department, and the data analyst posting usually lands on a founder or COO at exactly the moment the company crosses from gut feel to needing real numbers. The templates cover the most common versions of the role: general, junior, senior, business and operations, and marketing and e-commerce.
What Is a Data Analyst Job Description?
A data analyst job description is a document that explains the role's focus, responsibilities, required skills, data stack, work setup, and pay so you can post a job and attract qualified analysts. It typically covers a company summary, the questions the analyst will answer, key responsibilities, skills and tools, a salary range, and how to apply.
According to the Society for Human Resource Management's SHRM job description guide, a job description outlines the tasks, duties, and responsibilities of a position. For an analytics role, that outline should start with the business questions, not a keyword list.
Data analyst and data analytics job descriptions are the same posting: employers and candidates use the two phrasings interchangeably for an identical role. What genuinely differs is the focus and the seniority, which is why this page gives you five distinct versions instead of one generic hybrid. The role also sits next to related analyst titles.
If the work centers on requirements, processes, and systems rather than data and metrics, the business analyst templates are the better starting point. For budgeting and financial modeling, the financial analyst templates fit.
Which Template Should You Use?
Pick the template that matches the focus and seniority you are hiring for. The core structure is the same across all five, but each emphasizes the metrics, tools, and expectations that fit a specific version of the role. Use this guide to choose.
5 Free Data Analyst Job Description Templates
Download all five at once as separate Word files in one ZIP, or copy individual templates. Each one follows the same structure: company overview, job summary, key responsibilities, skills and qualifications, compensation, and how to apply. Fill in the brackets, especially the stack and salary fields, before you post.
Template 1: Data Analyst (General)
The universal baseline: reporting, dashboards, business questions, and data quality, with the stack and work-sample fields built in. Use this for most first analytics hires.
Template 2: Junior / Entry-Level Data Analyst
For an entry-level analyst who maintains reports, cleans data, and grows into owning analysis, with certificates and personal projects accepted as experience.
Template 3: Senior Data Analyst
For an experienced analyst who owns KPIs, the reporting foundations, and the recommendations, often as a one-person data team partnering directly with leadership.
Template 4: Business / Operations Data Analyst
For operational visibility: sales, costs, margins, and team performance pulled from your CRM, accounting, and operations systems into a reporting rhythm leadership uses.
Template 5: Marketing / E-commerce Data Analyst
For growth analysis: acquisition cost, funnel, retention, and channel performance, often the first analyst hire at e-commerce and subscription companies.
Data Analyst Duties and Responsibilities
Data analyst duties run from technical foundations to plain-language communication, and they fall into four categories. A good job description picks the specific duties that match your focus rather than listing every possible task.
The mix shifts by role: a junior analyst lives in reporting maintenance and data cleaning, a senior analyst weighs toward foundations and recommendations, and the business and marketing variants swap in their own metric sets.
Data Analyst vs Data Scientist
A data analyst answers business questions from existing data; a data scientist builds predictive models and machine learning systems. Analyst versus scientist is the most common confusion in analytics hiring. For most small and mid-sized companies, the first hire should be an analyst.
| Trait | Data Analyst | Data Scientist |
|---|---|---|
| Builds reports and dashboards to answer business questions | ||
| Builds predictive models and machine learning systems | ||
| Core toolkit is SQL, spreadsheets, and BI tools | ||
| Requires advanced statistics and engineering depth | ||
| Turns data into decisions the business acts on |
The titles blur in practice: the federal Standard Occupational Classification lists data analytics specialist and data mining analyst among its example titles for data scientists.
The hiring decision is still practical. If your questions are what happened, why, and what should we do next, post an analyst role from this page; if you need production machine learning, that is a scientist, a more expensive and usually later hire.
What to Include in a Data Analyst Job Description
Beyond the standard sections, an analyst posting lives or dies on three specifics: the business questions, the actual data stack, and the work-sample expectation. The duties themselves should be concrete enough that a candidate can picture the week.
| Weak bullet | Strong bullet |
|---|---|
| Work with data | Query, clean, and join data across our CRM, accounting, and web analytics |
| Create reports | Build and maintain the KPI dashboards leadership reviews weekly |
| Analyze trends | Run cohort and retention analysis to find where and why customers churn |
| Support the team | Turn one-off leadership questions into repeatable, documented reports |
| Present insights | Deliver findings as plain-language recommendations with clear next actions |
Specific duties and a named stack attract analysts who can do the work, and the work-sample ask lets you evaluate the craft directly, in the spirit of skills-based hiring. Keep the language neutral and inclusive: according to the Equal Employment Opportunity Commission, it is illegal to publish a job advertisement that favors or discourages applicants based on a protected characteristic.
If you want recognized occupational tasks to borrow, the Bureau of Labor Statistics duty list for data scientists covers the work an analyst role draws on: collecting and analyzing data, presenting findings with visualization software, and making business recommendations to stakeholders.
How to Write a Data Analyst Job Description
A strong data analyst job description takes about 20 minutes once you know which questions the hire will own. Here is the process the templates are built around.
Data Analyst Salary
Data analyst pay varies widely by seniority, industry, and remote policy. The government does not track the title separately, so anchor on the closest official category and adjust from your market.
Position your range against the level and the market: junior analysts sit well below the baseline, generalist and operations analysts in between, and senior analysts and marketing analysts with growth track records approaching or above it. Remote-friendly postings compete in a national market. Always publish the range: pay transparency laws increasingly require it, and experienced analysts skip postings without one.
Analyst roles are typically salaried and exempt from overtime, but according to the Department of Labor, job titles do not determine exempt status. The specific duties and the salary both have to meet the department's regulations, and the salary must be at least $684 a week. Check both as you structure the role.
Hiring Your First Data Analyst at a Small Company
Large companies hire analysts into existing data teams with data warehouses, documentation, and recruiting pipelines. A growing small company hires its first analyst into spreadsheets and disconnected systems, with the founder running the search personally. That difference should shape the posting more than anything else on this page.
From Hiring to Onboarding
The job description is step one. An analyst's first weeks are decided by two things you control before the start date: access and context. Access means accounts and permissions for every data source on day one: the CRM, accounting software, analytics tools, ad platforms, and the database. An analyst without access is an expensive observer.
Context means the questions leadership cares about, who owns which numbers today, and the spreadsheets currently running the business, handed over in an organized first week rather than discovered by archaeology. Set both up before they start. An offer letter template handles the offer, and an onboarding template structures the first weeks around access, context, and an early win.
FirstHR connects the offer, e-signature on agreements, document storage, and the onboarding workflow in one place, with task workflows for the access-granting steps across your systems, so a small company can take its first data hire from signed offer to first useful dashboard without an HR department.
Frequently Asked Questions
What does a data analyst do?
A data analyst turns a company's data into answers and decisions. Core duties include building and maintaining reports and dashboards, querying and cleaning data across systems, answering business questions with documented analysis, tracking KPIs with the teams that own them, and presenting findings in plain language. The day-to-day varies by focus: a business or operations analyst reports on sales, costs, and team performance from systems like the CRM and accounting software, while a marketing or e-commerce analyst owns funnel, acquisition cost, and retention metrics. In a small company, one analyst typically covers all of it and builds the reporting foundation from scratch.
What should a data analyst job description include?
A strong data analyst job description includes a company summary, the questions you need answered, 8 to 10 specific responsibilities, the required skills, the work setup, a salary range, and how to apply. Three details make the biggest difference. Name the systems and tools the analyst will work in, because candidates judge their own fit by your stack. Invite links to past analysis, since looking at real work is the best way to judge an analyst. And be candid about how mature your data is: for a first data hire, tell candidates they will set up the reporting from the ground up instead of taking over a finished system. Generic postings pull in keyword-heavy resumes, while specific ones pull in working analysts.
What is the difference between a data analyst and a data scientist?
A data analyst uses the data a business already has to explain what is going on and what to do about it, while a data scientist develops predictive models and machine learning tools. Day to day, the analyst delivers reports, dashboards, KPI tracking, and written analysis, working mainly in SQL, spreadsheets, and business intelligence software. The scientist needs deeper statistics and engineering skills, and the role pays more. The two labels overlap in the real world: the federal occupational coding system lists data mining analyst among the job titles under the data scientist occupation. Most small and mid-sized companies need the analyst. When your questions are what happened, why it happened, and what to do next, hire an analyst; when you need machine learning models running in production, you need a data scientist, which is usually a later hire.
Does a small business need a data analyst?
Usually not at first, and an honest look at that question is the right starting point for any job description. A full-time analyst starts to pay for itself once your data has outgrown your tools: systems that report conflicting numbers, the same leadership questions going unanswered, a rising bill for outside data consultants, or calls made on instinct that the numbers could have settled. Many companies reach that stage while growing from small to mid-size, and e-commerce, software, and other data-heavy businesses tend to get there sooner. Until then, sharper dashboards in the tools you already use, a fractional (part-time) analyst, or an operations hire with strong analytical skills often deliver more value than a full-time analytics salary.
What salary should I list for a data analyst?
Start from the closest government benchmark, then adjust for your market. The Bureau of Labor Statistics has no standalone occupation for data analysts. The nearest one it tracks is data scientists, whose median pay was $120,230 a year in May 2025, and BLS projects 35 percent growth for that occupation by 2035, one of the fastest rates in its projections. Generalist data analysts usually earn less than that median: junior analysts sit well under it, while senior analysts come close to it or pass it, and industry and remote policy can shift the figure significantly. Whatever range you choose, publish it. A growing number of states require pay transparency, and in a competitive analytics market, the experienced candidates you most want tend to skip postings that leave pay out.
What skills should I require for a data analyst?
Require the core toolkit and the communication, and treat the rest as trainable. The practical baseline is strong SQL, advanced spreadsheet skills, and experience with at least one BI or dashboard tool; Python or R is a meaningful plus for automation and deeper analysis but is not mandatory for most reporting roles. The skill that separates good analysts is translation: turning a vague leadership question into a concrete analysis, and turning the results back into plain language a non-technical team can act on. Evaluate it directly by asking for a work sample and judging the clarity as hard as the code. Degrees matter less than demonstrated work; certificates plus a real project beat credentials alone.
How do I write a data analyst job description for a small company?
Start with the questions the hire will answer, not the job title. Spell out what you need to know, such as which channels make money, why customers churn, and where margin leaks, and list the systems and tools you actually use so candidates can see what they are walking into. Be upfront about whether this is your first data hire and that the role means building the foundation. Limit the requirements to the toolkit the job really needs, meaning SQL, spreadsheets, and a BI tool, instead of a wall of keywords. Ask for a work sample, say clearly whether the role is remote, since so much analytics talent works remotely, and include the salary range. The five templates on this page are built for companies where the founder or COO handles this hire directly.
What happens after I hire a data analyst?
Once the offer is signed, focus on the two things a new analyst needs to be productive: access and context. Access is the new-hire paperwork plus working logins to each data source from the first day, including your database, CRM, accounting software, analytics tools, and ad platforms; without them, you are paying someone to watch. Context is a plan for week one that covers which questions leadership cares about, who is responsible for which numbers right now, and which spreadsheets the business actually runs on. FirstHR handles the offer letter, e-signature on agreements, document storage, and the onboarding checklist in one place, with task workflows for the access-granting steps, so a small company can take its first data hire from signed offer to first query without an HR department.