Data Engineer Salary in Minneapolis — 2026 BLS Data
Salary distribution
Percentile breakdown of Data Engineer base salaries in Minneapolis.
The $130,000 median base for a data engineer in Minneapolis is a reasonable starting point, but it flattens a market that spans entry-level pipeline builders at healthcare IT shops all the way to senior data platform architects at Target or UnitedHealth Group pulling $160K+ before bonuses. BLS OEWS May 2024 data for SOC code 15-1245 (Database Architects, which encompasses most data engineering roles in the survey) shows a national median of $135,980 — Minneapolis runs about 4% below that national figure, consistent with its slightly below-national-average tech wage premium versus coastal hubs. The P25-to-P90 range here — from $112K to $163K — is wide enough that your actual number will be determined almost entirely by company tier and technical specialty, not by which neighborhood you live in.
What the median hides
The $130K median number represents the statistical midpoint across all data engineering roles in the Minneapolis metro. That population includes analysts at regional insurance carriers who got the “data engineer” title without a substantial tooling overhaul, mid-career pipeline engineers at mid-sized retailers, and senior Databricks architects at major healthcare or financial services firms. They all get counted the same.
Three groups sit below the median that don’t belong in your reference point:
- Early-career engineers (under two years of experience) in Minneapolis average $75K-$90K. If you have three or more years building production pipelines, the median doesn’t describe you.
- Non-stack-specific roles at companies where “data engineer” means maintaining a legacy on-premise SQL Server warehouse with no cloud involvement. These positions rarely break $115K in Minneapolis.
- Contractor and staffing agency placements, which are included in OEWS data and are often benchmarked 10-15% below permanent hires for the same technical level.
If you’re a mid-level engineer with hands-on experience in at least one major cloud platform (AWS, Azure, or GCP) and a modern orchestration tool (Airflow, dbt, Prefect), the P50 for your actual peer group is closer to $135K-$145K. The $130K headline is the correct BLS anchor, but your reference band should be higher.
How Minneapolis compares to major data engineering hubs
Minneapolis is not San Francisco or Seattle, and the numbers reflect that honestly — but the story is more nuanced than a raw comparison suggests.
San Francisco / Bay Area median data engineer base sits around $175K-$200K based on BLS OEWS data and self-reported figures on Levels.fyi. The premium is real, but San Francisco’s cost-of-living index of approximately 178 means your purchasing power on $180K in SF is roughly equivalent to $104K in Minneapolis. A $130K Minneapolis salary actually buys more than a $180K SF salary in daily living terms.
Seattle runs about $155K-$170K median base for data engineers, anchored by Amazon, Microsoft, and a dense cluster of cloud-native companies. COL index around 148 — the Seattle-to-Minneapolis purchasing power gap shrinks from $40K nominal to about $15K real.
Austin is the closest comparable mid-tier market: $130K-$145K median base, COL index around 119. Austin has higher compensation because of the concentration of FAANG satellite offices (Apple, Google, Oracle) that pay coast-aligned bands. Minneapolis’s employer mix — dominated by healthcare, retail, and financial services rather than pure-play tech — keeps the ceiling lower but also means layoff waves hit less dramatically.
Chicago (150 miles south) averages around $135K-$145K for data engineers. The gap is modest enough that commuting to Chicago for a specific role is not irrational, though most Minneapolis engineers aren’t doing it.
The Minneapolis market’s real advantage is stability. The MSP metro’s top data engineering employers — UnitedHealth Group (the largest employer of data engineers in Minnesota), Target, Best Buy, 3M, Cargill, and US Bank — are long-tenured, profitable organizations with consistent headcount. The boom-bust hiring cycles that define SF and NYC are less pronounced here.
What drives the spread: company tier, level, and specialty
Three variables explain almost all of the gap between P25 and P90 in Minneapolis.
Company tier
Minneapolis doesn’t have a FAANG campus, but it has two tiers that span most of the market:
Fortune 500 / large enterprise (Target, UnitedHealth Group, 3M, US Bank, Best Buy, Ameriprise): These organizations pay in the $125K-$165K base range for data engineers. UnitedHealth Group in particular has built one of the largest data platforms in the healthcare sector — the Optum analytics division employs hundreds of data engineers — and pays competitively by Minneapolis standards. Expect structured leveling (associate, mid, senior, staff), annual merit increases of 3-5%, and bonus targets of 6-10% of base. Equity is mostly restricted to senior-level roles and above; cash compensation dominates.
Mid-market and regional (regional banks, insurance companies, healthcare networks, mid-sized retail): $105K-$135K base range. Less formal leveling, more variance in tooling maturity. A significant portion of the P25-P50 population lives here — these roles exist in volume but rarely break $140K without a title change.
Tech and high-growth companies with Minneapolis offices or remote presence: This includes national remote-first companies that post roles with “Minneapolis preferred” or hire MN residents, plus local growth companies like C.H. Robinson (logistics tech) and Datalink. Compensation here varies widely — national tech companies often pay coast-band rates for remote workers, which means some Minneapolis-based engineers earning $155K-$180K are technically in this cohort even though their W-2 reflects a MN address.
Level
Using the informal market levels common in Minneapolis’s employer base:
- Associate/entry data engineer (0-2 years): $75K-$95K
- Mid-level data engineer (2-5 years, owns pipelines end to end): $115K-$140K
- Senior data engineer (5-8 years, designs architectures, mentors): $140K-$165K
- Staff / lead data engineer (8+ years, cross-team platform influence): $160K-$190K
The senior-to-staff jump is where Minneapolis compensation compresses relative to coastal markets. A senior IC who would be an L6 staff engineer at a Bay Area company often runs out of upward comp trajectory in Minneapolis around $165K-$175K unless they move into management.
Technical specialty
Modern data stack skills carry a real premium in Minneapolis hiring. Based on job posting analysis and recruiter-reported ranges:
- Databricks / Apache Spark experience adds approximately $10K-$18K to offers. The Databricks Data + AI Summit 2024 showed a 47% year-over-year increase in enterprise Databricks adoption — Minneapolis’s financial services and healthcare sectors are actively migrating, and certified practitioners are scarce locally.
- dbt (data build tool) + Snowflake proficiency is increasingly required for mid-senior roles; engineers who can architect a full medallion pipeline in Snowflake with dbt transformations command toward P75.
- Real-time streaming (Kafka, Kinesis, Flink) is rarer in the Minneapolis market than batch/warehouse patterns. Engineers with genuine production Kafka experience can expect 10-15% above their non-streaming peers.
- Cloud data platform depth (AWS Glue + Redshift, Azure Synapse + Data Factory, or GCP BigQuery + Composer) — one deep specialization is baseline at this point; multi-cloud breadth at a senior level pushes offers to the high end of each level band.
Legacy BI/ETL skills (SSIS, Informatica, SAS) still get jobs at older enterprise shops in Minneapolis, but they cap out well below current-stack roles and are trending downward in posting volume.
Total compensation breakdown
BLS OEWS captures base salary only. For a mid-level data engineer at a large Minneapolis employer, the full picture looks like this:
Base salary: $130,000. This is the W-2 number and the figure employers use to anchor benefit calculations, 401(k) match percentages, and bonus targets.
Annual bonus: ~$9,000. Minneapolis’s dominant employer type — large enterprise and Fortune 500 — typically offers annual performance bonuses of 6-8% of base at mid-level. A $130K engineer with a 7% target bonus earns a $9,100 bonus in a normal performance year. Healthcare and financial services firms tend to hit targets more consistently than retail. Note that bonuses are variable and not guaranteed — during margin-pressure years (retail especially), bonuses get cut or eliminated.
Equity / RSUs: ~$14,000 annualized. This is where Minneapolis diverges most sharply from coastal tech. Most large Minneapolis employers (healthcare, retail, manufacturing) do not offer RSU grants to individual contributor data engineers below the senior or staff level. When equity exists, it’s typically smaller than coastal tech counterparts — a $56K initial four-year grant ($14K/year annualized) is in line with what senior-level IC roles at public companies like Target or Ameriprise report. Engineers at national tech companies hiring in Minneapolis can see larger equity packages — but those roles are benchmarked nationally, not locally.
Total target compensation: ~$153,000. That’s base + target bonus + annualized equity. For comparison, a senior-level Minneapolis data engineer with 6+ years of experience and Databricks/cloud specialization is realistically targeting $155K-$185K total comp at a top-paying employer. The P90 ceiling at $163K base corresponds to total comp around $185K-$200K for engineers who’ve reached staff level at a UnitedHealth or similar.
Benefits that matter in Minneapolis: The large healthcare employers here (UnitedHealth, Allscripts, Optum) offer employer-sponsored health plans with unusually low employee contribution rates — some engineers report paying under $100/month for family coverage. That’s worth $10K-$20K annually in pretax value compared to market-rate premiums. Pension plans and profit-sharing (3M, Cargill) add another layer that purely cash-focused comparisons miss.
Cost-of-living adjusted reality
Minneapolis’s COL index sits around 103 on a US-average-equals-100 scale — essentially at parity, with slightly elevated transportation and grocery costs offset by housing costs that are meaningfully below coastal markets. A two-bedroom in Minneapolis proper (Uptown, North Loop, Northeast) runs $1,600-$2,200/month in 2024-2025; comparable square footage in Seattle runs $2,400-$3,200, and in San Francisco $3,200-$4,500.
The purchasing power math:
| City | Median Base | COL Index | Purchasing Power (vs. Minneapolis) |
|---|---|---|---|
| Minneapolis | $130,000 | 103 | baseline |
| Austin | $135,000 | 119 | -5% vs. Minneapolis |
| Seattle | $162,000 | 148 | +4% vs. Minneapolis |
| San Francisco | $185,000 | 178 | +1% vs. Minneapolis |
The table shows something counterintuitive: a Minneapolis data engineer at $130K has nearly identical purchasing power to a San Francisco engineer at $185K, and roughly equivalent to a Seattle engineer at $162K. The advantage over Austin is marginal in COL-adjusted terms despite Austin’s nominally higher salary.
Where the model has limits: Minneapolis winters impose real costs — higher utility bills (heating oil, gas), all-season tires, and the psychic toll of January. These don’t show up in COL indices. Offsetting: Minnesota has a functional public transit corridor along the Green and Blue light rail lines connecting the airport, downtown, and both downtowns (Minneapolis and St. Paul), which reduces car dependency for engineers living along those corridors.
Minnesota’s income tax rate is one of the highest in the country — the top marginal rate hits 9.85% on income above $183,340 (single filers in 2024). A $130K single filer pays roughly 7.05% effective state income tax. That’s about $3,500-$5,000 more in state tax per year than an equivalent earner in Austin or Seattle (which have no state income tax). Factoring state income tax into take-home, the real purchasing power advantage narrows further relative to Texas and Washington.
Three-lever negotiation playbook
Minneapolis’s data engineering market is less competitive on the hiring side than coastal hubs — many roles get relatively few qualified applicants at senior levels — which gives candidates more room to negotiate than the “take it or leave it” dynamic at high-volume SF startups. These three levers are specific to the Minneapolis market.
1. Anchor to the current-stack talent premium, not the job posting range
Large Minneapolis employers — Target, UnitedHealth Group, US Bank — often post data engineering roles with wide bands ($100K-$155K) that leave enormous room within the range. When the recruiter asks for your number, do not anchor to the midpoint. Instead, anchor explicitly to your stack: “I have four years of production Databricks experience and a current dbt + Snowflake certification. Based on the market premium for that combination in Minneapolis, I’m targeting $148K.” You’ve named your P75 with a specific technical justification rather than a general salary claim. Recruiters at large employers have the most pushback authority against “I want more” and the least authority against “comparable Databricks engineers in Minneapolis are at this number.”
2. Target the bonus target percentage, not just the base
Most Minneapolis data engineers negotiate base and ignore the bonus target rate. This is a mistake. A $5,000 improvement to annual bonus target (from 7% to 10% of a $130K base) is $3,900/year — the same as a $3,900 raise, but it comes out of a different budget and often has less resistance from hiring managers. At financial services firms and healthcare companies in Minneapolis, asking to be placed in the next bonus tier up (e.g., from “IC grade 3” to “IC grade 4” targeting 10% versus 7%) is a legitimate ask for a strong candidate and moves total comp meaningfully without touching base salary bands.
3. Get the remote/hybrid policy in writing before you sign
Minneapolis’s data engineering market has become increasingly national — you’re competing for the same candidates as Chicago, Denver, and remote-first companies. Several large Minneapolis employers have pulled back on remote flexibility post-2022 (Target, notably, has enforced a four-day in-office requirement as of late 2024). If your offer assumes in-office work, the implicit cost of commuting, work attire, and reduced flexibility is real compensation. Counter-offering for one additional remote day per week, or for a remote option 2-3 times per month for travel, is now a common ask that often succeeds without touching the salary number. Frame it as schedule flexibility rather than remote work — the language matters at legacy enterprise employers.
Data caveats
BLS OEWS is the gold standard for base salary data — it’s survey-mandatory for covered employers, not opt-in like Glassdoor or LinkedIn — but its limitations are material here:
“Data engineer” is not a BLS occupation code. BLS classifies most data engineers under SOC 15-1245 (Database Architects) or 15-1252 (Software Developers), depending on how the employer wrote the job description for the survey. This means the OEWS data for “data engineers” is an approximation assembled from adjacent SOC codes. The Minneapolis metro percentiles cited here are derived from BLS OEWS May 2024 data for SOC 15-1245 in the Minneapolis-St. Paul-Bloomington MSA (MSA code 33460), cross-referenced against multi-source aggregators (Salary.com, ZipRecruiter, Robert Half) that explicitly track the “Data Engineer” title in the Minneapolis market.
BLS excludes equity. For most Minneapolis data engineering roles, this matters less than in SF — equity is a smaller fraction of comp here. But for engineers at national tech companies hiring remotely in Minneapolis, BLS will understate total comp by 10-20%.
Lag. May 2024 data reflects wages paid during the May 2024 survey reference period. By mid-2026, base salaries at top employers have moved 5-8% from those reported levels. Adjust upward accordingly for current offers.
Sample size in the Minneapolis metro. The Minneapolis-St. Paul MSA is not a primary tech hub, which means OEWS cell counts for specific occupations like Database Architects can be small enough that BLS suppresses some percentile figures. Where exact BLS metro figures are unavailable, the state-level (Minnesota) estimates are a reasonable proxy — Minnesota’s tech salary distribution is heavily weighted toward the Twin Cities metro.
For the most current triangulation, combine BLS percentiles with Minnesota Department of Employment and Economic Development (DEED) wage data (mn.gov/deed) and active job posting ranges from employers like Target and UnitedHealth Group, which now disclose pay ranges in postings under Minnesota’s expanded pay transparency requirements effective January 2025.