Data Analyst Salary in Dallas — 2026 BLS Data
Salary distribution
Percentile breakdown of Data Analyst base salaries in Dallas.
The $92,000 median base for a Data Analyst in Dallas is a reasonable starting point for a mid-career hire at a corporate employer — but the BLS data that anchors that figure (SOC 15-2031, Operations Research Analysts, May 2024 national median: $91,290) tells you almost nothing about where you personally should sit. The spread from P25 to P90 runs $73K to $140K inside one metro area, a gap that reflects industry, seniority, tool fluency, and company type more than anything inherent to the Dallas job market. Before you use any single number in a negotiation, you need to know which segment of that range actually applies to your profile.
What the median hides
BLS OEWS is the most rigorous public wage source in the US — mandatory reporting, tens of millions of workers, standardized methodology — but the occupation bucket it uses for Data Analysts (15-2031, Operations Research Analysts, or the newer catch-all 15-2098) lumps together a 22-year-old doing Excel reporting at a regional insurance carrier and a senior analytics engineer writing dbt pipelines at AT&T’s consumer data platform. Both are “data analysts.” They are not paid the same.
In Dallas specifically, this creates a bimodal market. The lower mode is corporate back-office analytics: regulatory reporting, marketing attribution, operational dashboards. Roles in this tier cluster between $65K and $85K. The upper mode is what the industry now calls “data engineering-adjacent analytics” — roles where SQL fluency, Python, and at least one cloud data warehouse (Snowflake, BigQuery, Redshift) are table stakes, and where the output is less “here is a chart for the VP” and more “here is a production pipeline that powers the business.” Those roles start around $95K and top out well above $120K before you add any seniority.
The median at $92K sits at the crossover point between those two modes. If your role looks like the first description, the median is your ceiling as a mid-level hire. If it looks like the second, it’s roughly your floor.
How Dallas compares to other major hubs
Dallas is not a top-tier data analyst market by raw salary, but it competes well on purchasing power. The national picture for BLS SOC 15-2031 (May 2024):
- San Francisco / Bay Area: median $120K–$135K base, driven by tech-company density and cost-of-living escalation in comp bands
- New York City: $110K–$125K, anchored by finance (Goldman Sachs, Citi, JPMorgan all have significant DFW presences, but their NY offices pay more)
- Seattle: $105K–$118K, Amazon/Microsoft halo effect
- Austin: $94K–$100K median — Austin edges Dallas by roughly $8–10K on average, partly because the Austin market skews more toward tech-native startups
- Dallas: $92K median
- Houston: $88K–$92K, energy-sector concentration, somewhat different skill mix
The gap between Dallas and San Francisco looks large in absolute terms — roughly $35–40K — but narrows considerably once you apply COL adjustment (see below). The gap between Dallas and Austin is real but modest. If you’re deciding between DFW offers and Austin offers from the same tier of company, location preference will matter more than the salary delta.
One underappreciated Dallas dynamic: the concentration of corporate headquarters. AT&T, American Airlines, Toyota’s North American HQ, McKesson, and Comerica all run large analytics teams here. These employers pay in the $85K–$110K band for mid-level roles, offer competitive benefits, and tend toward stability over high-variance startup compensation. If you’re coming from a coastal tech company and targeting a similar tech employer, Dallas has a thinner pool — but it’s growing.
What drives the spread: company tier, level, and specialty
Three variables explain most of the P25-to-P90 range:
Company tier. A data analyst at a Fortune 50 corporate HQ (AT&T, McKesson) typically earns $85K–$108K at mid-level, with structured salary bands and predictable annual increases. A comparable role at a venture-backed fintech or healthtech startup may pay $92K–$120K with equity that’s illiquid but nonzero. A role at a large consulting firm (Deloitte, Accenture, EY all have DFW presences) often lands $78K–$95K — the trade-off being training, credential, and exit optionality. The differences aren’t random: tier correlates with how much business value the analytics team demonstrably creates and how scarce the skills are.
Level / scope. Entry-level (0–2 years, primarily SQL and visualization): $58K–$74K. Mid-level (3–5 years, Python or R, some modeling, dashboard ownership): $82K–$105K. Senior (6+ years, stakeholder influence, cross-functional project ownership, possible direct reports): $108K–$130K. Lead or analytics manager: $125K–$155K. Seniority is the single largest salary lever inside any one company, and in Dallas the step-up from mid to senior is more meaningful than in markets where total comp is dominated by equity.
Specialty. The skill stack matters more than the job title. A generalist data analyst with Tableau and Excel skills is the commodity end of the market. Add dbt, Snowflake, and the ability to write production-quality Python, and you’re looking at a 15–25% premium. Add machine learning fluency (sklearn, feature engineering, model evaluation) and you start competing with data scientist postings. Healthcare analytics with HIPAA/claims data experience commands a premium in DFW given the density of hospital systems (UT Southwestern, Baylor Scott & White, Texas Health Resources). Financial analytics (credit modeling, fraud, risk) pays above median at the banking and insurance employers concentrated in the Irving/Las Colinas corridor.
Total compensation breakdown
Unlike San Francisco or New York, Dallas data analyst compensation is heavily weighted toward base salary. The typical structure for a mid-level hire at a corporate employer:
- Base salary: $92,000. This is what BLS measures and what shows up in most salary survey data. It’s also the most negotiable component at mid-level.
- Annual cash bonus: ~$8,000. Most corporate employers target 8–12% of base for individual contributor analysts, paid annually and tied to company and personal performance. Bonuses are more reliable at large profitable companies (AT&T, airlines during profitable quarters) and less so at startups or companies with variable earnings. Eight thousand dollars is a realistic average across a mixed population of employers — you’ll find ranges from $3K to $18K depending on industry and year.
- Equity: ~$2,000 annualized. Equity is functionally irrelevant for most Dallas data analyst roles. Publicly traded employers occasionally grant small RSU awards to senior ICs, but they’re uncommon below the senior level and the values are modest compared to coastal tech. Startups grant options, but sub-$10K annualized is typical for analytics roles that aren’t director-level or above. If equity is a priority, the DFW market is not the right geography unless you’re targeting a specific high-growth company.
- Total comp: ~$102,000. The $8K bonus and $2K annualized equity bring the realistic total to about $102K for a mid-level professional. Senior roles ($120K base) can reach $135K–$145K total with bonuses, though the equity component rarely moves the needle.
One benefit often overlooked in total comp comparisons: Dallas employers in healthcare, finance, and utilities tend to offer strong 401(k) matching (4–6% common) and fully employer-paid health premiums, which add $8K–$15K in economic value that standard salary surveys don’t capture.
Cost-of-living adjusted picture
Dallas’s C2ER/ACCRA composite COL index landed at 101.6 in Q2 2024 — essentially exactly at the US national average of 100. Housing is the main variable: a one-bedroom in central Dallas runs $1,600–$1,900/month, which is expensive relative to smaller metros but dramatically cheaper than San Francisco ($3,200–$3,800) or New York ($3,000–$3,600). No state income tax in Texas adds another 3–5% to effective take-home relative to California (13.3% marginal rate), New York (10.9%), or Oregon (9.9%).
The COL-adjusted math for a $92K Dallas base:
- At US average COL (index 100), $92K buys roughly the same basket of goods and services it nominally states.
- To match the purchasing power of $92K in Dallas, a San Francisco employer needs to pay about $164K (COL index 178.6 ÷ 102 × $92K).
- That same $92K in Dallas has roughly the same purchasing power as $110K in Austin (COL 119.3).
What this means practically: if you’re a data analyst comparing a $95K Dallas offer to a $115K Austin offer, the Austin offer looks better on paper but only amounts to about $8–10K more in actual purchasing power after housing and taxes. Whether that’s worth relocating depends on your specific housing and lifestyle costs, not the headline number.
Three-lever negotiation playbook
Lever 1: Name the market band, not a single number. Recruiters at corporate employers typically work from salary bands that are wider than their initial offer. When you’re given an offer below P50, the strongest response is a specific range anchored to data: “Based on BLS OEWS May 2024 data for this occupation in the Dallas metro, combined with comparable job postings in this role and tool set, the market range for this scope sits between $92K and $105K. I’d like to discuss landing in the upper half of that band.” This frames you as data-literate — relevant when the job is literally data analysis — and gives the recruiter a justifiable number to bring to their manager.
Lever 2: Push on bonus structure, not just base. Base salary is frequently constrained by grade bands that require HR approval to exceed. Bonus target percentage is often more flexible, especially at companies that tie it to individual performance metrics rather than a fixed percentage. Asking to increase the bonus target from 8% to 12% of base adds $3,700 to your expected annual comp and often requires less approval than a base bump of the same size. If the company has consistently paid above-target bonuses, that history is worth asking about explicitly.
Lever 3: Create leverage with a competing offer or a deadline. The data analyst market in Dallas is active but not frenzied in 2026 — employers are not panicking over candidate shortages the way they were in 2021–2022. The most effective negotiation tool remains a competing offer from a comparable employer. Even a verbal offer letter you expect to receive within two weeks gives you a timeline to share. If you don’t have a competing offer, a clearly stated deadline (“I need to make a decision by [date] because I have other processes underway”) accomplishes part of the same function by creating urgency without requiring you to produce a paper offer you don’t have.
One additional tactic specific to corporate HQ roles in Dallas: if the employer has a formal compensation review cycle (most large companies do in Q1 or Q2), you can negotiate a shorter time to first review as a compromise when base flexibility is limited. Getting your review at 6 months instead of 12 is worth $4K–$6K on average if you get a standard 4–6% increase.
Data caveats
A few things worth knowing before you take any of these figures to a negotiation:
BLS occupational classification is imprecise. The agency does not have a single unified SOC code for “Data Analyst.” Most data analyst work rolls up into 15-2031 (Operations Research Analysts) or 15-2051 (Data Scientists), depending on how the employer classified the role when they filed their OEWS survey. This means the BLS percentiles in this page reflect a heterogeneous population. Job titles matter less than the actual work scope and the tool set, which is why cross-referencing BLS data with posted salary ranges and platform data (Glassdoor, Levels.fyi for tech-adjacent roles) gives you a more accurate picture than any single source.
The data is lagged. BLS OEWS May 2024 data was released in late 2024 and measures wages paid approximately 18–24 months before you read this in mid-2026. The Dallas market has seen steady demand and modest wage growth in data roles since then; adjust upward by 5–8% for roles posted today versus the figures cited here.
Total comp surveys over-sample tech. When you see “data analyst median total comp in Dallas: $115K” from a crowdsourced platform, the respondents skew heavily toward tech-adjacent roles and people who actively sought out a salary benchmarking tool — both of which skew compensation upward. BLS OEWS skews in the other direction, capturing a broader employer universe including many roles that would not surface in tech-focused salary data. The truth for any individual role sits somewhere between the two, calibrated by your specific employer tier, specialty, and level.
Track your offers and pipeline, not just your salary. The number on your offer letter is one data point. The number of competing offers you have, how quickly companies are moving through the process, and which companies ghosted you after initial screening all tell you something about your market value that salary surveys cannot. OfferFlow’s job tracker lets you keep all of that signal in one place — offers, rejections, and pipeline stages — so you can spot patterns and time your negotiations rather than reacting to individual offers in isolation.