These US Cities Offer Software Engineers the Most Home Buying Power

Tech companies are known for offering competitive salaries to software engineers (SWEs), which often translates into massive home-buying power. However, as home prices continue to rise in many regions, even high-paying roles are not immune to broader housing market constraints.

Fullstack Academy’s latest analysis examines the home-buying power of software engineers across the largest U.S. cities. By comparing the salaries for local (small to medium-sized companies) and Big Tech (national and global companies) SWEs with home prices, our analysis highlights where these professionals can afford homes — and where rising prices present challenges, further illuminating the dire state of home affordability in the nation.

Yet, with the continued prevalence of remote work, the landscape is shifting, offering many SWEs greater flexibility in choosing where to live. This shift has a substantial impact on home affordability for many of these professionals, allowing them to explore housing markets that are extraordinarily more affordable than traditional tech hubs.

Using data from Levels.fyi, Redfin, Tax Foundation, and Value Penguin, our analysis applies the 28/36 rule (a common-sense approach to calculate the amount of housing debt an individual should take on) to determine how much house is affordable for both local SWEs in the city where they work and for major tech companies like Google, Amazon, and OpenAI across the nation.

Read on to see how your city compares and how much of an advantage local or Big Tech salaries provide when it comes to buying a home today.

Key Takeaways

• Detroit, St. Louis, and Pittsburgh offer the greatest home affordability surplus for local SWEs.

• SWEs in Southern and Western cities like Phoenix and Seattle have buying power that matches median home prices with a 1:1 ratio.

• California is home to the most cities where SWEs have a home affordability deficit.

• Meta and OpenAI are the only Big Tech companies where a SWE can afford a median-priced home in any major U.S. city.

Home Affordability for Local Software Engineers

While software engineers (SWEs) are very well-compensated, their ability to afford homes varies across the U.S. The broader challenge of housing affordability affects many professionals, sometimes including SWEs. As home prices outpace income growth in many U.S. tech hubs, SWEs are now unable to afford a median-priced home in over one-third of the largest U.S. cities. This dramatic fact highlights the growing challenges faced by many prospective homebuyers across the country.

Cities Where Software Engineers Have a Home Affordability Surplus

However, there are many cities where SWEs enjoy affordable housing. In Southern and Western cities such as Phoenix and Seattle, local SWEs are able to buy homes that closely align with the 28% rule, enjoying a near-perfect 1:1 ratio between their buying power and local home sales prices. Case in point: The median salary of a local SWE in Austin, Texas, allows them to afford a $622,670 house, while the median sale price is only $453,755.

Meanwhile, local SWEs in midwest and rust belt cities like St. Louis and Pittsburgh fare even better, with salaries that secure homes nearly double the median sale price. For example, a SWE in Detroit can afford a $463,735 house where the median sale price is only $201,750.

Cities Where Software Engineers Have a Home Affordability Deficit

Conversely, the high cost of coastal city living is a significant challenge for many local SWEs. Cities like San Francisco and San Jose, California, are well-known for their astronomical real estate prices, and even local SWEs struggle to live there.

In these major coastal tech hubs, SWEs can barely afford a home that is half of the median home price. In San Francisco, the median home sale price is over $1,500,000, and the median SWE salary can only afford a home that sells under $866,125 to stay within the 28% rule.

It’s also not just on the West Coast that SWEs run into housing affordability issues. In Boston, SWEs can only afford a home that is one-third under the median sale price. In Jersey City, New Jersey, the median home price is just under $800,000, while the median SWE salary can only pull off a home worth just under $500,000.

Big Tech Software Engineers and Their Home-Buying Power

While the Big Tech home affordability story for software engineers (SWEs) working at companies like Meta, Amazon, and Apple is much more optimistic, even these extremely well-paid professionals can encounter home prices that are far outside the 28% rule of thumb.

For starters, only Meta, Amazon, and OpenAI SWEs can afford a house in the same city as their company headquarters. The median salary for Meta SWEs who want to live near company headquarters in San Francisco translates into a maximum affordable home of $1,696,732. While that may seem like a lot, it’s only a little more than the median home sale price of $1,510,000.

Meanwhile, Google, Apple, and Microsoft SWEs are priced out of the housing market where company headquarters are. A Google SWE can afford a $1,102,092 house in San Jose, California, but the median home price is a whopping $1,578,792. Apple headquarters are in the same city, and their SWEs are also short $582,833 in buying power just to afford the median home in that city.

While Microsoft SWEs are close to affording the median-price home near company headquarters in Seattle, these professionals still surpass the 28% rule by $25,246 when buying a median-priced home in this city.

To illustrate how extreme housing affordability is for even Big Tech SWES, we can compare the buying power of these tech superstars to local SWEs around the nation.

A Meta SWE working and living in San Francisco earning a median salary of $435,000 has as much buying power as a local SWE in Glendale, Arizona, earning $123,000. An Apple SWE working and living in San Jose, California, earning $280,000, has as much buying power as a local SWE in Jersey City, New Jersey, earning $182,500.

However, for Big Tech SWEs working remotely or outside headquarters, their hefty compensation packages translate into massive buying power around the nation. For example, an OpenAI SWE can afford a $3.64M home in Cincinnati, where the median home price is only $299,375.

A Google SWE who wants to buy a home in Cleveland will have the pick of the market. Their median salary allows a maximum affordable home of $1.32M, and the median home sale price is just $238,223. Amazon SWEs can buy a house in Louisville, Kentucky, that is four times the median sale price of $275,450.

The degree to which Big Tech SWEs struggle to afford homes near their company headquarters and the massive buying power those same salaries translate to in other major cities around the U.S. highlight the enormous disparity in the nation’s housing market.

Biggest Winners and Losers in Software Engineer Home Affordability

Detroit stands out as the city where software engineers (SWEs) have the most home-buying power, both for local SWEs living in Detroit and Big Tech companies. A local SWE in Detroit can afford a home well over double the median home sale price. Big Tech SWEs buying in Detroit can pull off a house several times the median home value. At the extreme, an OpenAI SWE could buy 18 houses in Detroit and still be under the 28% rule.

Out of all the local and Big Tech SWE salaries in our analysis, OpenAI SWEs have the greatest absolute buying power. In fact, OpenAI and Meta SWEs are the only Big Tech SWEs that can afford a median-priced home in any major U.S. city when following the 28% rule.

On the opposite end of the spectrum, SWEs in California’s coastal cities face the toughest markets. In the most challenging market for an SWE to afford, Irvine, California, local SWEs can’t even buy a home worth one-third the median sale price. The median SWE salary can only afford a $443,437 house in Irvine, where the median home sells for $1,600,000.

Home sales prices are so steep in Irvine that even most Big Tech SWEs cannot afford to buy a house there. The median salary across all Big Tech SWEs doesn’t even purchase two-thirds of a median-priced home in the city. Google, Amazon, Apple, and Microsoft SWEs are totally priced out of the market, with many unable to afford even half the median-priced home.

Where Software Engineers Are Paid the Most

While the tech industry is known for its high salaries, some companies stand out even amongst the heavyweights for their eye-popping median compensation. Using data from Levels.fyi, we found the tech companies that pay their software engineers (SWEs) the most.

Topping the list is OpenAI, the AI research company behind ChatGPT. Their median compensation of $798,000 for SWEs is by far the highest among all the tech companies in our analysis. Next, but far behind OpenAI, is Coupang, the South Korean e-commerce giant, which pays the second-highest median SWE salaries at $603,380.

Snap and Netflix are also heavy hitters, landing #3 and #4 by paying $540,000 and $450,000, respectively. The rising value of SWE in the finance and trading industries is also reflected in the list with Citadel and Hudson River Trading. Citadel, a hedge fund, ties with Netflix for #4 with their median compensation of $450,000. Hudson River Trading, a quantitative trading firm, lands #6 with their $437,500 median SWE compensation.

From Coding to Closing

Especially in a competitive housing market, gaining the right skills to become a software engineer can significantly boost your ability to purchase a valuable home. To best equip yourself with the top expertise sought by both local and national companies, Fullstack Academy’s Full-Time Software Engineering Bootcamp can help set you on the path to a higher salary.

Whether your goals are to work for a Big Tech company like Amazon and Meta or to position yourself for large payoffs in up-and-coming tech hubs, Fullstack Academy provides the training and tools you need to secure roles that turn high salaries into homeownership. No matter where you want to live, we’ll help you find the right bootcamp to set you on the right path to achieve both your career and homeownership goals.

Methodology

In September 2024, we assessed the home-buying power of software engineers (SWEs) in the 60 largest cities in the U.S. To accomplish this, we utilized compensation data from Levels.fyi, real estate data from Redfin, property tax data from the Tax Foundation, and property insurance rate data from Value Penguin.

We focused our analysis on determining the maximum affordable home price for both local and Big Tech SWEs. To do so, we used the 28% housing debt-to-income ratio rule. This rule is commonly used in financial guidelines, suggesting that homeowners should not allocate more than 28% of their gross monthly income toward housing expenses. For our analysis, housing expenses include principal, interest, taxes, and insurance (PITI).

Software Engineer (SWE) Compensation

We sourced median compensation data from Levels.fyi for SWEs across various metropolitans and all experience levels in the U.S. The compensation data includes base salary, bonuses, and stock options, ensuring a full representation of an SWE's total earnings.

Levels.fyi aggregates data by metropolitan area. We applied the salaries for each metro to the individual cities on our list. For the most accurate comparison, we eliminated cities from the analysis that do not have a minimum of 50 SWE salaries reported. We also collected the national median compensation for SWEs at the following Big Tech companies: Google, Meta, Amazon, Apple, and Microsoft.

Home Sales Price, Taxes, and Insurance

We sourced 12-week rolling average median home sale prices from Redfin across various cities in the U.S. Local property tax rates were sourced from the Tax Foundation. Property insurance rates were based on data from Value Penguin, expressed as a percentage of total home value for $350,000 in dwelling coverage.

Max Affordable Home and Buying Power Ratio

For each city in our analysis, we computed the monthly housing budget for each SWE median compensation in each city using the collected and calculated PITI data. The budget was set at 28% of median SWE compensation to follow the 28/36 rule of thumb for housing affordability.

We then used this monthly budget plus a 20% down payment to calculate the total maximum affordable home for each local SWE compensation-housing market pairing. Then, we computed a buying power ratio for each compensation-housing market pairing by dividing the maximum affordable home by the median sales price in each city.

In addition to analyzing local SWE buying power, we also calculated the buying power for SWEs at several Big Tech companies. For each Big Tech SWE, we computed the maximum affordable home price using their median total compensation and compared their buying power across multiple U.S. cities. This allowed us to evaluate how far a Big Tech salary stretches in both high-cost areas such as San Francisco and more affordable metros like Detroit.