Data Engineer Salary in Dallas — 2026 BLS Data
Salary distribution
Percentile breakdown of Data Engineer base salaries in Dallas.
The $120,840 median base for a data engineer in Dallas-Fort Worth comes directly from BLS OEWS May 2024 data for the Dallas-Fort Worth-Arlington MSA, covering SOC 15-2051 (Data Scientists and related data engineering roles). That number is honest — it includes everyone from a junior pipeline builder at a regional insurance carrier to a principal data architect at AT&T’s headquarters in downtown Dallas. The 2x spread between P25 and P90 ($84,710 to $172,160) is not statistical noise; it reflects real structural differences in employer type, stack maturity, and seniority level. Understanding those differences is what separates a well-calibrated offer acceptance from leaving $20,000-$40,000 on the table.
What the median hides
$120,840 is a reasonable midpoint for a data engineer with three to six years of experience working at a mid-market Dallas employer — think a regional financial services firm, a healthcare system, a logistics company. But the distribution is skewed enough that the median can mislead in both directions.
On the low end, the P25 of $84,710 reflects roles at smaller employers, roles that are labeled “data engineer” but are functionally closer to analyst or BI developer work, and entry-level positions where the pipeline responsibility is limited to ELT jobs in a single cloud environment. If you see a posting from a 200-person company asking for “Tableau, SQL, and some Python experience” and titling it data engineer, that role is almost certainly below the median — and the comp will reflect it.
On the high end, the P90 of $172,160 is a base-salary figure for senior data engineers, architects, and lead platform engineers at large, data-mature organizations — Toyota’s North American headquarters in Plano, McKesson’s Irving campus, and the large financial services infrastructure in downtown Dallas (Goldman Sachs, Bank of America, JPMorgan all have significant engineering presence in DFW). At P90 and above, equity and bonus begin to matter meaningfully, which the BLS number does not capture.
The P75 of $140,840 is the most actionable benchmark for a mid-senior engineer with six to ten years of experience and cloud-platform ownership. If you have demonstrable production experience with Spark, dbt, Airflow, or a modern lakehouse stack — and you can show measurable impact (pipeline latency reduction, cost optimization, data quality SLAs) — P75 should be your floor in a DFW negotiation, not a stretch target.
How Dallas compares to other tech hubs
Dallas is not San Francisco. But it is not a second-tier market either, and the gap has narrowed considerably as major employers have doubled down on DFW as a cost-optimized alternative to coastal engineering centers.
The national BLS OEWS May 2024 median for this SOC code is roughly $112,590. Dallas at $120,840 runs about 7.3% above the national median — a modest but meaningful premium that reflects the DFW labor market’s concentration of corporate headquarters and the competition for experienced data engineers across telecom, financial services, healthcare IT, and logistics.
Compare that to:
- Austin, TX: Median around $131,000-$134,000 across job-board aggregates, reflecting the Meta, Apple, and Tesla engineering office presence. Austin commands a roughly 8-10% premium over Dallas on base, but its COL has risen sharply since 2021.
- Houston, TX: Closer to $122,000-$128,000 median. The energy sector (oil and gas, utilities) is a heavy consumer of data engineering talent, but the pay bands tend to run slightly narrower than DFW.
- Seattle, WA: Median around $155,000-$165,000, driven by Amazon (one of the world’s largest data engineering employers), Microsoft, and a dense cloud-native ecosystem. The premium is real, but Washington’s lack of a state income tax partially offsets what looks like a bigger gap.
- San Francisco/Bay Area: Median around $160,000-$180,000 base, plus significant equity at FAANG-adjacent employers. COL-adjusted, the premium nearly evaporates — more on that below.
The Dallas sweet spot: you earn comfortably above the national median, you pay no state income tax (Texas), and your dollar goes further than in Austin, Seattle, or the Bay Area. For data engineers who are not chasing FAANG equity upside, DFW frequently wins on net take-home.
What drives the P25-to-P90 spread
Three factors explain most of the variance in Dallas data engineer pay:
Company tier and data maturity. AT&T, which employs thousands of engineers in downtown Dallas, pays Senior Data Engineers in the $135,000-$170,000 range with bonus. American Airlines, headquartered in Fort Worth, has a large data platform organization that runs comparable bands. Toyota’s North American headquarters in Plano has aggressively built out its data and analytics infrastructure since relocating from California and pays at the higher end of the DFW market. At the other end, regional businesses — mid-size retailers, healthcare networks, property management companies — that are earlier in their data journey often pay $80,000-$105,000 for roles that involve significant manual work and limited cloud-native tooling. Consulting and IT services firms (large ones have significant DFW delivery centers) pay modestly above the P25 and make up a meaningful share of data engineering job volume in the market.
Seniority and scope. BLS lumps a junior engineer building their first Airflow DAG with a principal architect designing a multi-domain data mesh. The real ladder in DFW looks roughly like this: Junior/Associate (0-2 years): $75,000-$95,000; Mid-level (3-5 years): $100,000-$130,000; Senior (6-10 years): $130,000-$160,000; Staff/Principal (10+ years or broad platform ownership): $160,000-$195,000. Each step carries expectations: senior means you own production reliability, not just builds. Staff means you set the architecture direction, not just implement it.
Specialty and stack. Not all data engineering is priced the same. Engineers with deep cloud platform expertise — particularly Snowflake, Databricks, or native AWS/Azure data services — command a 10-20% premium over generalist SQL-and-Python engineers in DFW. Real-time streaming expertise (Kafka, Flink, Spark Structured Streaming) is consistently undersupplied relative to demand in the Dallas market, where financial services and telecom firms need low-latency pipelines. ML platform engineering — building the feature stores, training infrastructure, and model serving pipelines that feed data science teams — commands the highest premium in the market, often 20-30% above median for comparable seniority.
Total compensation breakdown
The BLS base figures are the foundation, but total comp at competitive DFW employers adds two meaningful layers:
Bonus. Most large employers in Dallas operate annual bonus programs tied to company and individual performance. For data engineers, target bonus percentages typically run 8-15% of base. A mid-senior engineer at $130,000 base with a 10% target bonus earns $13,000 in additional cash in a normal year. Financial services firms and healthcare systems often run 12-15% targets; energy and logistics companies tend to be at the lower end.
Equity. This is where Dallas differs most from coastal markets. The majority of data engineering employers in DFW are large public companies or private non-startup firms — AT&T, McKesson, American Airlines, Toyota, Kimberly-Clark — where equity exists (RSU grants are common at publicly traded employers) but rarely dominates the package the way it does at early-stage tech companies. A senior data engineer at a DFW-headquartered public company might receive $40,000-$80,000 in RSU grants vesting over three to four years — a meaningful supplement but not the 2-3x multiplier you see at FAANG or pre-IPO tech. For the typical DFW data engineer role, budgeting $12,000-$20,000 in annualized equity is realistic. CBRE, which has its global headquarters in Dallas and is aggressively building data platform capabilities, is one employer offering closer to coastal equity packages as it competes for talent.
For a senior data engineer at a competitive DFW employer — $130,000-$140,000 base, 10-12% bonus, and RSU grants annualizing around $15,000-$20,000 — total annual compensation runs $155,000-$175,000. That is the realistic benchmark for “I’m being paid fairly at a good employer” at the mid-senior level.
Cost-of-living adjusted value
Dallas carries a C2ER Cost of Living Index of 101.7 — essentially at par with the US national average. That is the single most important number in this analysis for anyone comparing DFW to other tech markets.
San Francisco’s COL index is approximately 178.6. A $160,000 base in San Francisco has the same purchasing power as roughly $91,000 at US average — or $89,500 in Dallas. Put another way: a $120,840 Dallas data engineer base goes as far as approximately $211,900 in San Francisco. The coastal premium in nominal salary does not survive the COL adjustment.
Austin’s COL index has risen to approximately 119.3 as of 2024. A $131,000 Austin median base adjusts to roughly $109,800 in equivalent purchasing power — modestly below the Dallas adjusted value, despite the higher nominal figure. The Austin premium exists and is real, but it is smaller than the job-board headlines suggest once housing and transportation costs are factored in.
Texas also has no state income tax. That is a flat, unambiguous benefit worth 4-9% of gross compensation depending on which state you are comparing against. A New York data engineer earning $155,000 pays 6.85% state income tax plus local NYC tax; a Dallas engineer at the same base keeps all of it. On a $130,000 base, that is roughly $8,900 per year in additional take-home relative to most coastal states.
For data engineers evaluating relocation or remote-work flexibility: the COL-and-tax adjusted case for staying in or relocating to Dallas is strong unless you are specifically targeting pre-IPO equity upside or FAANG-tier total comp, which currently requires being in the Bay Area, Seattle, or New York.
Three-lever negotiation playbook
Lever 1: Anchor to the P75, not the median. Most hiring managers in DFW anchor their mental model of “fair data engineer salary” somewhere around the median or slightly below. The BLS P75 of $140,840 is a defensible, sourced number — not an aggressive ask. When you receive an initial offer, ask for the job posting’s salary range if it was not disclosed (Texas does not mandate pay transparency, but many large employers post ranges voluntarily), then position your ask relative to P75 with a concrete rationale: years of experience, specific stack match, and one or two measurable outcomes from prior roles. “Based on BLS data for this metro, senior data engineers at the 75th percentile earn around $140,000 — given my Databricks platform experience and the pipeline reduction work I led at [company], I’m targeting $138,000” is a cleaner ask than a number without a frame.
Lever 2: Price your stack premium explicitly. If you have production Databricks or Snowflake experience, real-time streaming depth, or ML platform work, do not let that remain implicit. Spell it out in writing during negotiation. A recruiter at a financial services firm knows they have been unable to hire a Kafka-fluent data engineer for six months; connecting your ask to that specific scarcity gives them a reason to go back for approval on a higher band. The premium for genuine real-time streaming expertise in DFW is routinely $15,000-$25,000 above the standard senior band.
Lever 3: Negotiate the RSU grant, not just the base. Base salary bands at large DFW employers are usually managed with limited flexibility — HR has guardrails and recruiters rarely have unilateral authority to move more than 5-8% from the initial offer. RSU grants are often negotiated separately and have more discretion at the individual manager and total-comp committee level. If you cannot move the base, ask for an increased initial equity grant or an accelerated vesting schedule. On a four-year $60,000 RSU grant, asking for $80,000 adds $5,000 per year — a meaningful number that is often within the manager’s approval authority without requiring an escalation to HR leadership.
Data caveats
A few important limitations on everything above:
BLS OEWS captures base wages only. Bonus, equity, and profit-sharing are excluded. For DFW’s large-employer market — where total comp typically runs 20-35% above base — the BLS percentiles understate actual total compensation.
The May 2024 survey data is lagged. You are reading this in 2026; the technology labor market has moved since May 2024. DFW data engineering demand has continued to grow as major employers — Toyota, Goldman Sachs, AT&T — expand their data platform teams. Budget for a 5-8% upward adjustment to the BLS figures when negotiating in 2026.
SOC 15-2051 combines data scientists and data engineers. BLS does not publish a separate SOC code exclusively for data engineers; the closest match is 15-2051, which also captures data scientists and some machine learning practitioners. Pure pipeline-and-infrastructure data engineers and ML-focused data scientists often have different pay bands, and the combined code blurs that distinction. Cross-reference with job board data (Indeed, Built In DFW, LinkedIn) for role-specific benchmarks.
Job-board aggregates skew high. Glassdoor, Salary.com, and ZipRecruiter figures for Dallas data engineers tend to land $20,000-$30,000 above BLS figures because they draw from self-reported salary data at companies where employees are more likely to be at well-paying employers. Neither source is wrong — they measure different things. BLS is the more conservative, survey-mandated floor; job-board data captures what the market is offering at active-hiring employers. The real answer is usually between the two.
Use OfferFlow’s job tracker to log the offers you receive alongside their compensation details — tracking across five or six conversations makes it immediately obvious when a number is off-market, and having a structured log turns anecdote into leverage at negotiation time.