Two data engineers. Same city. Same years of experience. Same tech stack — Python, Spark, Airflow.
One makes $118,000. The other makes $195,000. The $118K engineer works at a healthcare company, negotiated once during hiring, and hasn't looked at compensation data since. The $195K engineer works at a fintech startup, negotiated equity on top of base, and benchmarks their pay every six months.
Same skills. 65% pay gap. And the $118K engineer has no idea they're leaving $77,000 on the table every single year.
How much do data engineers make?
The BLS reports a $112,590 median annual wage for data scientists (the closest federal category). Platform sources that track the 'Data Engineer' title directly report higher: Glassdoor at $131,152 median total pay and Salary.com at $133,536 median base. The consensus range across sources is $120K–$134K for mid-career data engineers.
What is the entry-level data engineer salary?
Entry-level data engineers (less than 1 year of experience) earn approximately $97,540 on average according to Built In. Salary.com places the 10th percentile at $107,550. Expect $95K–$110K in base salary for your first data engineering role, with location being the biggest variable.
What is the senior data engineer salary?
Senior data engineers average $143,076 according to Built In. Salary.com's 75th percentile (where most senior engineers fall) is $147,129. At top-tier tech companies, senior data engineers earn significantly more through stock and bonus — total compensation at FAANG-level firms often exceeds $200K.
Where do data engineers earn the most?
San Francisco pays the highest average at $161,823, followed by remote roles at $148,600 and Colorado at $139,002 (Built In). The BLS reports that data scientists in computer systems design earn $128,020 — the highest-paying industry category.
There's no single "data engineer salary." Different sources measure different things — base salary vs. total compensation, specific job title vs. broader occupational category, self-reported vs. employer-verified. Understanding these differences is essential for benchmarking your own pay.
Multi-Source Salary Model
Why four sources? Because no single source captures the full picture. Each has different methodology, sample size, and compensation definitions.
| Source | Tier | What's Measured | Median / Average | Sample |
|---|---|---|---|---|
| BLS OOH | Tier 1 (Government) | Base wage — Data Scientists (SOC 15-2051) | $112,590 median | 233,440 workers (OEWS survey) |
| Glassdoor | Tier 3 (Platform) | Total pay (base + bonus + equity) — 'Data Engineer' title | $131,152 median total / $103,699 base | 26,000+ salary submissions |
| Salary.com | Tier 3 (Comp Data) | Base salary — 'Data Engineer' title | $133,536 median | Employer-reported comp data |
| Built In | Tier 3 (Tech Platform) | Base salary — 'Data Engineer' title | $125,976 avg base / $150,372 avg total | Anonymous tech employee submissions |
The consensus across four independent sources: mid-career data engineers earn $120K–$134K in base salary, with total compensation (including bonus and equity) pushing $130K–$150K. The BLS number is lower because it blends data engineers with adjacent roles.
Experience is the single biggest salary lever. The jump from entry-level to senior is substantial — roughly 45-50% — and it compounds further at staff and principal levels.
Data Engineer Salary by Experience Level
Average annual base salary in USD
| Level | Typical Experience | Salary Range | Source |
|---|---|---|---|
| Entry-level | <1 year | $97,540 avg | Built In |
| 10th percentile | Early career | $107,550 | Salary.com |
| 25th percentile | 1-3 years | $119,934 | Salary.com |
| Median (50th) | 3-5 years | $133,536 | Salary.com |
| Senior Data Engineer | 5-7 years | $143,076 avg | Built In |
| 75th percentile | Senior+ | $147,129 | Salary.com |
| Data Engineering Manager | 7+ years | $164,123 avg | Built In |
| 90th percentile | Staff/Principal | $159,505 | Salary.com |
| BLS top 10% | All levels (Data Scientists) | $194,410+ | BLS OOH |
- Entry-level ($97K): Execute tasks, learn the stack, build one pipeline end-to-end. Proving reliability matters more than speed.
- Mid-level ($120K–$134K): Own systems independently. Design data models, handle on-call, mentor juniors. This is where salary jumps fastest.
- Senior ($143K–$147K): Architect systems, make technology decisions, lead cross-team projects. The premium reflects decision-making responsibility.
- Staff/Principal ($160K–$195K+): Set technical direction for the organization. At this level, base salary is often just 50-60% of total compensation — equity becomes the dominant component.
The biggest salary jump happens between mid-level and senior — roughly $15K–$20K. Getting there takes 2-3 years of owning end-to-end systems and making independent architectural decisions.
Location creates the widest salary gaps in data engineering. A data engineer in San Francisco earns ~$35K more than one in a mid-market city — but cost of living often absorbs the difference.
Data Engineer Average Salary by City
Average annual base salary in USD
Since 2020, the shift to remote work has compressed geographic salary differences for data engineers. Many companies now use national pay bands or tiered location systems (Tier 1: SF/NYC/Seattle, Tier 2: Austin/Denver/Boston, Tier 3: everywhere else) with 10-15% gaps between tiers instead of the 30-40% gaps that existed pre-pandemic.
San Francisco still pays the most ($162K average), but remote roles at $149K are the best deal when adjusted for cost of living. The geographic premium is shrinking as more companies adopt national pay bands.
The same data engineering role pays differently depending on where you work. The BLS OEWS breaks this down by industry for the Data Scientists category:
| Industry | Mean Annual Wage | vs. Overall Median |
|---|---|---|
| Computer systems design & services | $128,020 | +14% |
| Management of companies & enterprises | $126,940 | +13% |
| Scientific research & development | $120,090 | +7% |
| Consulting (management & technical) | $110,240 | -2% |
| Insurance carriers | $108,920 | -3% |
- Tech companies and consultancies (computer systems design) pay the most — this includes FAANG, enterprise software, and systems integrators
- Corporate data engineering (management of companies, insurance) pays competitively but with lower upside — more stability, less equity
- The industry gap is ~$20K between the highest and lowest BLS categories — that's a real difference in annual income for the same skill set
The BLS industry categories don't isolate fintech or quantitative finance, but these sectors are known for aggressive data engineering compensation. Hedge funds and high-frequency trading firms regularly pay $200K+ total compensation for senior data engineers who can build low-latency data pipelines.
Industry choice can swing your salary by $20K+ for the same role and experience level. Tech and finance pay the most; government, education, and non-profits pay the least.
Base salary is only part of the story. For mid-level and senior data engineers, total compensation includes three components:
| Component | What It Includes | Typical Range |
|---|---|---|
| Base salary | Fixed annual pay | $104K–$134K (Glassdoor/Salary.com median) |
| Annual bonus | Performance-based cash | $2K–$25K (Built In: avg $24,396 additional cash) |
| Equity / RSUs | Stock grants vesting over 3-4 years | $0–$80K+/yr (varies massively by company) |
- Glassdoor: $131,152 median total pay ($103,699 base + $27,453 bonus/equity)
- Salary.com: $139,433 average total cash ($133,536 base + $5,897 bonus)
- Built In: $150,372 average total comp ($125,976 base + $24,396 additional cash)
At companies like Google, Meta, Amazon, and Netflix, senior data engineers regularly receive $60K–$100K+ in annual equity on top of a $160K–$180K base. This pushes total compensation to $250K–$350K — but these roles are highly competitive and represent the top ~5% of the market.
Base salary accounts for 60-80% of total compensation for most data engineers. The remaining 20-40% comes from bonus and equity — and this variable portion grows dramatically at senior levels and at equity-heavy companies.
How does data engineering compensation compare to adjacent roles? This context helps if you're choosing between paths or considering a transition.
| Role | BLS Median (May 2024) | BLS SOC Code | Growth (2024-2034) |
|---|---|---|---|
| Data Scientists (incl. Data Engineers) | $112,590 | 15-2051 | 34% |
| Software Developers | $131,450 | 15-1252 (combined) | 17% |
| Computer & Info Research Scientists | $140,910 | 15-1221 | 25% |
| Database Architects | $142,620 (mean) | 15-1243 | — |
| Operations Research Analysts | $91,290 (OOH) | 15-2031 | 21% |
| Market Research Analysts (DA proxy) | $76,950 | 13-1161 | 7% |
- Data Engineer vs Software Engineer: Software developers have a higher BLS median ($131,450 vs $112,590) because the BLS software developer category is narrower and more precisely defined. In practice, platform sources show data engineers and software engineers earn comparably — the Glassdoor median for data engineers ($131K) is nearly identical to the BLS software developer median.
- Data Engineer vs Data Analyst: Data engineers earn significantly more. The closest BLS proxy for data analysts (Market Research Analysts) shows a $76,950 median — roughly $36K less. Glassdoor shows $131K vs $108K for the specific titles.
- Data Engineer vs Data Scientist: In the BLS, they're the same category. In practice, compensation is similar, with data scientists having slightly higher base salaries at some companies but data engineers having more consistent demand.
Data engineers earn more than data analysts (~$23K–$36K gap depending on source) and comparably to software engineers. The role sits in the upper tier of tech compensation, with the bonus of faster-than-average job growth (34%).
Beyond experience and location, several factors create salary variation within the same job title.
Cloud Platform Expertise
AWS, Azure, and GCP certifications and hands-on experience command premiums. Companies migrating to the cloud pay more for engineers who can design cloud-native architectures from scratch.
Streaming and Real-Time Skills
Data Modeling and Architecture
Programming Depth
Production-grade Python, Scala (for Spark), and strong SQL optimization skills drive higher compensation. The more languages and paradigms you can work in at production quality, the more you're worth.
Certifications
Cloud certifications (AWS Data Engineer, Azure Data Engineer, Databricks) provide the clearest verifiable signal for hiring managers. While the direct salary premium is hard to isolate, certified engineers tend to land roles at higher-paying companies.
The highest-paid data engineers combine cloud expertise, real-time streaming skills, and strong data modeling fundamentals. Depth in one area beats breadth across many — specialize, then expand.
Data is your best negotiation tool — and as a data engineer, you should be better at using it than most.
1. Know Your Market Number
Use the multi-source data in this guide to establish your target. Cross-reference:
- BLS OOH for the government baseline ($112,590 median for the category)
- Glassdoor for title-specific total pay ($131,152 median)
- Salary.com for percentile ranges ($120K 25th, $134K 50th, $147K 75th)
- Built In for city-specific data (adjust for your market)
2. Anchor on Total Compensation
Don't negotiate base salary alone. Ask about:
- Sign-on bonus — one-time cash to bridge the gap between current and new comp
- RSU/equity grants — especially at public companies where the value is liquid
- Annual bonus target — what percentage, and is it guaranteed for year one?
- Review timeline — can you get an accelerated 6-month review instead of 12?
3. Leverage Competing Offers
The strongest negotiating position is having a competing offer. Even if you prefer Company A, an offer from Company B gives you concrete leverage. Data engineering talent is in high demand — if you have the skills, getting multiple offers is realistic.
4. Quantify Your Impact
When negotiating a raise (not a new hire), come with data:
- Pipeline uptime improvements
- Query performance optimizations (from X seconds to Y)
- Cost savings from cloud infrastructure changes
- Data quality improvements that prevented downstream issues
The most effective salary negotiation combines external market data (this guide) with internal impact data (your results). Lead with numbers — it's what data engineers do.
- 01Mid-career data engineers earn $120K–$134K base salary across four independent sources (BLS, Glassdoor, Salary.com, Built In)
- 02Entry-level starts at $97K–$108K; senior roles reach $143K–$147K; top-10% earners clear $160K–$194K+ in base alone
- 03Total compensation (base + bonus + equity) pushes the median to $131K–$150K, with top-tier tech companies reaching $250K+ for senior engineers
- 04San Francisco ($162K), remote roles ($149K), and Colorado ($139K) are the highest-paying markets
- 05Computer systems design ($128K) and management of companies ($127K) are the highest-paying BLS industries
- 06The field is growing 34% through 2034 (BLS) — over 10x the national average — keeping demand and salaries strong
- 07Negotiate using multi-source data: BLS for baseline, Glassdoor for title-specific pay, Salary.com for percentiles, Built In for city benchmarks
How much does a data engineer make per hour?
Based on the BLS OEWS May 2024 data, data scientists (the category including data engineers) earn a median of $54.13 per hour. The mean hourly wage is $59.90. For the specific 'Data Engineer' title, Salary.com's median of $133,536 annually translates to roughly $64/hour.
Is data engineering a six-figure career?
Yes, for most professionals. Even entry-level data engineers earn approximately $97K–$108K. By mid-career (3-5 years), nearly all data engineers are well into six figures. The BLS reports that even the 25th percentile for the broader data scientist category is $79,810 — and platform sources tracking the specific 'Data Engineer' title show higher numbers.
Do data engineers make more than software engineers?
Compensation is comparable. The BLS reports a $131,450 median for software developers vs $112,590 for data scientists (the broader category). But platform sources tracking the specific 'Data Engineer' title (Glassdoor: $131K) show nearly identical pay to the BLS software developer median. At the same company, a data engineer and a software engineer at the same level typically earn the same.
What is the data engineer salary in New York City?
Built In reports an average data engineer salary of $129,927 in New York City. This is slightly below the national average for the role because NYC has a large number of data engineers across all experience levels and industries, including lower-paying sectors. Senior roles at NYC-based financial institutions and tech companies pay significantly above this average.
How much do FAANG data engineers make?
Senior data engineers at FAANG companies (Meta, Apple, Amazon, Netflix, Google) typically earn $250K–$350K+ in total compensation, with base salaries of $160K–$190K and equity grants of $60K–$120K annually. These represent the top of the market and are highly competitive roles.
Does a master's degree increase data engineer salary?
It can, but the effect is smaller than in data science or research roles. The BLS notes that data scientists 'typically need at least a bachelor's degree' with some employers preferring a master's. In practice, a strong portfolio of production data engineering work and relevant cloud certifications often matter more for salary than a master's degree.
Is data engineering a good career financially?
Yes. The BLS projects 34% job growth through 2034 — over 10x the national average. The median salary exceeds $112K (BLS) to $133K (Salary.com), with clear progression to $160K–$194K+ at senior levels. Combined with strong demand and multiple career paths (management, architecture, freelance), data engineering is one of the strongest financial career choices in tech.
Prepared by Careery Team
Researching Job Market & Building AI Tools for careerists · since December 2020
- 01Occupational Outlook Handbook: Data Scientists — U.S. Bureau of Labor Statistics (2025)
- 02National Employment and Wage Data (OEWS), May 2024 — U.S. Bureau of Labor Statistics (2025)
- 03Data Engineer Salaries — Glassdoor (2024)
- 04Data Engineer Salary in the United States — Salary.com (2025)
- 05Data Engineer Salary in US — Built In (2026)