Jacobs Solutions (J) Operating Expenses (2009 - 2026)
Jacobs Solutions' Operating Expenses came in at $524 million for fiscal Q3 2026 (quarter ended Jun 26, 2026), up 0.1% from $523.4 million a year earlier but down 40.2% from the prior quarter.
Jacobs Solutions (J) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 26, 2026, Jacobs Solutions reported Operating Expenses of $2.49 billion, up 18.2% year-over-year; for FY2025 (ended Sep 26, 2025), it was $2.12 billion, down 0.9% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 0.7% (FY2020 to FY2025).
- Going back by fiscal year, Operating Expenses was $2.14 billion in FY2024 (+5.2%), $2.03 billion in FY2023 (-0.3%), $2.04 billion in FY2022 (-13.4%) and $2.36 billion in FY2021 (+14.9%).
- The five-year range for quarterly Operating Expenses is $158.03 million (fiscal Q4 2022) to $876.07 million (fiscal Q2 2026).
- Year-over-year, Operating Expenses has increased for four consecutive quarters, with growth averaging 20.7% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q4 2024 (growth of 99.6%), and the weakest in fiscal Q4 2022 (a decline of 72.6%).
- Business Quant data shows J's Operating Expenses at $876.07 million (Q2 2026), $532.69 million (Q1 2026) and $555.36 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 80.21 Bn | 78.29 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 35.53 Bn | 13.78 Bn | - | - |
| 3 | Emcor | 28.47 Bn | 24.87 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Jacobs Solutions | 17.08 Bn | 11.74 Bn | 810.70 Mn | 524.00 Mn |
| 5 | Mastec | 13.07 Bn | 11.86 Bn | 556.28 Mn | 292.57 Mn |
| 6 | Sterling Infrastructure | 10.65 Bn | 8.98 Bn | 289.96 Mn | 65.66 Mn |
| 7 | IES Holdings | 8.49 Bn | 7.35 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Stantec | 8.13 Bn | 7.06 Bn | 1.36 Bn | 972.05 Mn |
| 9 | Aecom | 7.64 Bn | 2.76 Bn | -34.04 Mn | 46.45 Mn |
| 10 | Dycom Industries | 6.31 Bn | 5.45 Bn | - | - |
Historic Data
| Date | Value |
|---|---|
| Jun 26, 2026 | 524.00 Mn |
| Mar 27, 2026 | 876.07 Mn |
| Dec 26, 2025 | 532.69 Mn |
| Sep 26, 2025 | 555.36 Mn |
| Jun 27, 2025 | 523.40 Mn |
| Mar 28, 2025 | 529.70 Mn |
| Dec 27, 2024 | 512.85 Mn |
| Sep 27, 2024 | 538.92 Mn |
| Jun 28, 2024 | 549.96 Mn |
| Mar 29, 2024 | 528.72 Mn |
| Dec 29, 2023 | 522.73 Mn |
| Sep 29, 2023 | 270.04 Mn |
| Jun 30, 2023 | 587.00 Mn |
| Mar 31, 2023 | 600.43 Mn |
| Dec 30, 2022 | 576.91 Mn |
| Sep 30, 2022 | 158.03 Mn |
| Jul 1, 2022 | 558.71 Mn |
| Apr 1, 2022 | 704.20 Mn |
| Dec 31, 2021 | 619.14 Mn |
| Oct 1, 2021 | 576.25 Mn |
Jacobs Solutions Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=J&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "J", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=J&period=max&api_key=YOUR_API_KEY");
const data = await res.json();