Data analysts in the US earn $55,000-$160,000+ depending on experience, location, and industry. Entry-level: $55K-$75K. Mid-level: $75K-$100K. Senior: $100K-$130K. Lead/Director: $130K-$160K+. Tech and finance pay the highest premiums. The three biggest salary levers are experience level, industry, and location — in that order.
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How much do data analysts make?
The average data analyst salary in the United States is approximately $75,000-$85,000 in 2026, with a full range of $55,000 (entry-level) to $160,000+ (lead/director level). The Bureau of Labor Statistics reports a median salary of $83,800 for operations research analysts, the category that includes data analysts. Actual compensation varies significantly by experience, industry, and location.
What is the starting salary for a data analyst?
Entry-level data analysts (0-2 years of experience) typically earn $55,000-$75,000 in the US. The range depends on location (major metros pay 20-30% more), industry (tech and finance pay above average), and qualifications (a bachelor's degree or strong portfolio with certifications). The Google Data Analytics Certificate alone doesn't guarantee the top of this range — portfolio projects and domain knowledge push salaries higher.
Can data analysts make $100K?
Yes. Senior data analysts (5+ years) at tech companies or in major metropolitan areas typically earn $100,000-$130,000. Product analysts and specialized roles (financial analytics, healthcare analytics) at mid-to-large companies regularly exceed $100,000 at the mid-senior level. The fastest paths to $100K: specialize in a high-paying industry, develop Python/advanced analytics skills beyond basic SQL, and target senior or lead roles.
Salary articles are the most-searched content in any career cluster — and the most misleading. The numbers you see on job boards mix junior and senior roles, conflate different metro areas, and often include total compensation (with bonuses and stock) as if it's base salary. This guide uses sourced data, segmented by the variables that actually matter.
- Data Analyst Salary
The average data analyst salary in the United States ranges from $55,000 at the entry level to over $160,000 at the director level in 2026. The Bureau of Labor Statistics reports a median of $83,800 for operations research analysts. The three largest salary determinants are experience level, industry (tech and finance pay 15-25% premiums), and geographic location.
A few important notes about salary data: BLS data is the most reliable but lags by 1-2 years. Glassdoor data is more current but relies on self-reporting. The ranges below combine multiple sources for the most accurate picture available.
Data analyst salaries range from $55K to $160K+ in the US. The median is approximately $83,800. Experience level is the single biggest determinant — more than industry or location.
| Level | Years | Salary Range | What Drives the Jump |
|---|---|---|---|
| Junior Data Analyst | 0-2 | $55,000-$75,000 | Building independence — handling ad-hoc requests without hand-holding |
| Data Analyst | 2-4 | $75,000-$100,000 | Ownership — running recurring reports, designing dashboards, leading small projects |
| Senior Data Analyst | 4-7 | $100,000-$130,000 | Business impact — analyses that change decisions, cross-functional influence |
| Lead / Principal Analyst | 7-10 | $130,000-$160,000 | Strategic scope — defining metrics, building team processes, executive partnerships |
| Analytics Manager / Director | 10+ | $150,000-$200,000+ | Team leadership — hiring, strategy, organizational influence |
The jump from junior to mid-level is the fastest — typically 1-3 years. The salary increase (roughly $20K-$30K) is driven by proving you can work independently. The jump from senior to lead takes longer (2-4 years) because it requires shifting from execution to strategy — a fundamentally different skill set.
One critical note: The biggest salary jump in a data analyst's career often comes not from a promotion, but from a job change. Internal raises average 3-5% annually. Switching companies typically yields 10-20% increases at the same level.
Experience level is the primary salary driver. The fastest salary growth happens in the first 5 years. After senior level, further growth requires either specialization, management, or strategic company changes.
Location creates some of the widest salary gaps in data analysis. The same role at the same level can pay $30K-$50K differently depending on metro area.
| Metro Area | Junior Range | Mid-Level Range | Senior Range | Cost of Living Adjustment |
|---|---|---|---|---|
| San Francisco / Bay Area | $75K-$95K | $95K-$125K | $125K-$160K | Very high CoL offsets premium |
| New York City | $70K-$90K | $90K-$120K | $120K-$155K | High CoL offsets premium |
| Seattle | $70K-$85K | $85K-$115K | $115K-$145K | High CoL, strong tech market |
| Chicago | $60K-$75K | $75K-$100K | $100K-$130K | Moderate CoL, good value |
| Austin | $60K-$78K | $78K-$105K | $105K-$135K | Growing tech hub, moderate CoL |
| Atlanta | $55K-$72K | $72K-$95K | $95K-$125K | Lower CoL, growing analytics market |
| Dallas / Fort Worth | $55K-$70K | $70K-$95K | $95K-$125K | Low CoL, strong finance sector |
| National Average (Remote) | $55K-$70K | $70K-$90K | $90K-$120K | Typically 10-20% below top metros |
The cost-of-living trap: A $90K salary in San Francisco leaves less disposable income than a $70K salary in Atlanta. Before chasing the highest nominal salary, run the numbers on housing, taxes, and living costs. Sites like NerdWallet's Cost of Living Calculator make this easy.
Location premiums of 20-40% exist in major tech hubs but are often offset by higher cost of living. The best salary-to-cost ratio is typically in mid-size metros with growing tech scenes — Austin, Chicago, Atlanta, and Dallas offer strong value.
The industry you work in can be as impactful as your experience level. Tech and finance consistently pay the most. Government and nonprofit pay the least but offer benefits that reduce the total compensation gap.
| Industry | Salary Premium vs. Median | Why |
|---|---|---|
| Tech (FAANG, startups, SaaS) | +15-25% | High margins, data-centric products, intense competition for talent |
| Financial Services / Fintech | +10-20% | Revenue-critical analytics, regulatory requirements, high-stakes decisions |
| Healthcare / Pharma | +5-10% | Specialized domain knowledge, regulatory data, growing demand |
| Consulting (Big 4, boutique) | At median | Compensates with faster career progression and broader experience |
| Retail / E-commerce | At median to -5% | Large datasets but lower margins; strong for product and marketing analytics |
| Government / Nonprofit | -10-20% | Lower pay but strong benefits, stability, pension, work-life balance |
The strategic play: If your primary goal is maximizing salary, target tech or finance. If your goal is maximizing learning speed, target consulting (fast progression, broad exposure). If you want meaningful work and stability, healthcare and government offer underrated value.
Tech and finance pay 15-25% above median. Government and nonprofit pay below but compensate with benefits and stability. The industry premium can equal 2-3 years of experience in salary impact.
Understanding where data analysis sits relative to adjacent roles helps you make informed career path decisions.
| Role | Entry-Level | Mid-Level | Senior | What Drives Higher Pay |
|---|---|---|---|---|
| Data Analyst | $55K-$75K | $75K-$100K | $100K-$130K | Business impact, dashboard design, stakeholder communication |
| Business Analyst | $55K-$75K | $75K-$105K | $105K-$140K | Project management, requirements gathering, process improvement |
| Data Scientist | $80K-$110K | $110K-$150K | $150K-$200K+ | Statistical modeling, ML, experimentation, PhD premium |
| Data Engineer | $80K-$110K | $110K-$145K | $145K-$190K+ | Pipeline architecture, cloud infrastructure, scale |
| Product Analyst | $65K-$85K | $85K-$115K | $115K-$150K | Experiment design, user behavior, product impact |
Key observation: Data analysis has the lowest entry barrier but also the lowest salary ceiling among these roles. The pathways to higher compensation are: (1) specialize into product analytics, (2) move into data science (requires statistical modeling skills), (3) move into data engineering (requires infrastructure skills), or (4) move into management.
For detailed role comparisons and progression options, see Data Analyst Career Path. For salary negotiation strategies, see How to Negotiate Salary.
Data science and data engineering pay significantly more at every level, but require deeper technical skills (ML/statistics and infrastructure engineering, respectively). Data analysis offers the most accessible entry point with a clear — if lower-ceiling — progression path.
Remote data analyst roles are widely available, but they come with a salary trade-off.
The typical adjustment: Remote roles pay 10-20% less than equivalent on-site positions in high-cost metros (SF, NYC, Seattle). However, they often pay 5-15% more than the same role in a mid-size city. The net impact depends entirely on where you live.
The trend: Hybrid arrangements (2-3 days in office) are becoming the default at mid-to-large companies. Fully remote roles are increasingly common at startups and tech-first companies. Fully on-site is rare for data analyst positions in 2026.
Remote data analyst roles are widely available but typically pay 10-20% less than top-metro on-site positions. The salary-to-cost ratio often favors remote work from mid-cost cities. Hybrid is becoming the default at larger companies.
Five strategies, in order of impact:
1. Switch companies every 2-3 years early in your career. Internal raises average 3-5%. Job changes yield 10-20% at the same level. This is the single most effective salary lever in years 1-7.
2. Specialize in a high-paying domain. "Data analyst" is a generic title. "Product analyst at a fintech company" commands a premium. Healthcare analytics, financial analytics, and product analytics consistently pay above general data analysis.
3. Add Python to your SQL. Analysts who code in Python earn 10-15% more than SQL-only analysts at the same experience level, because they can handle automation, larger datasets, and more complex analysis.
4. Target the right industries. Tech and finance pay 15-25% premiums. If salary is your priority, orient your job search toward these sectors.
5. Negotiate every offer. Most data analyst candidates accept the first number. A 10-minute negotiation conversation can add $5K-$15K to your starting salary — that compounds across your career.
For salary negotiation scripts and strategies, see our How to Negotiate Salary guide — with templates you can use verbatim.
The fastest salary growth comes from strategic job changes, specialization, and adding Python to your SQL toolkit. Internal promotion is the slowest path to higher compensation — external moves yield 10-20% increases.
- 01Data analyst salaries range from $55K (entry) to $160K+ (director) in 2026, with a national median around $83,800
- 02Experience level is the primary salary driver — the first 5 years produce the steepest growth curve
- 03Tech and finance pay 15-25% above median; government and nonprofit pay 10-20% below but compensate with benefits
- 04Location premiums of 20-40% exist in SF/NYC/Seattle but are largely offset by cost of living
- 05Data science and data engineering pay more at every level — the trade-off is accessibility of entry
- 06The five biggest salary levers: strategic job changes, specialization, Python skills, industry targeting, and negotiation
What is the highest-paying data analyst role?
Analytics directors and VP-level analytics leaders at tech companies earn $180,000-$250,000+ in total compensation. Among individual contributor roles, product analysts at FAANG companies and senior financial analysts at investment banks earn the highest — typically $130,000-$170,000 at the senior level. Specialization in a high-margin industry is the single biggest lever for maximizing analyst compensation.
Do data analysts get bonuses?
Yes, most mid-level and senior data analyst roles include bonuses. Typical bonus ranges: 5-10% of base salary at mid-level, 10-15% at senior level, and 15-25% at director level. Tech companies may also offer stock options or RSUs, which can add $10,000-$50,000+ to total compensation at senior levels. Entry-level roles less commonly include bonuses.
Is a data analyst salary enough to live on?
In most US cities, yes. An entry-level salary of $55K-$75K is above the national median household income. However, in high-cost metros like San Francisco or New York City, an entry-level data analyst salary requires careful budgeting — especially for housing. Mid-level salaries ($75K-$100K) provide comfortable living in most locations.
How fast do data analyst salaries grow?
Data analyst salaries typically grow 8-15% per year in the first 5 years (combining merit raises and job changes). After senior level, growth slows to 3-8% per year unless you move into management or switch companies. The biggest salary jumps come from role changes (company switches) rather than internal promotions.
Do data analysts make more than accountants?
At the entry level, they're similar ($55K-$75K for both). At mid and senior levels, data analysts in tech and finance tend to earn more than accountants in traditional firms. However, CPAs at Big 4 firms can exceed $150,000 at the manager level. The comparison depends heavily on industry and specialization for both roles.
Prepared by Careery Team
Researching Job Market & Building AI Tools for careerists · since December 2020
- 01Occupational Outlook Handbook: Operations Research Analysts — Bureau of Labor Statistics, U.S. Department of Labor (2024)
- 02Occupational Employment and Wages: Operations Research Analysts — Bureau of Labor Statistics (2023)
- 03Data Analyst Salaries — Glassdoor (2025)