Tetra Tech (TTEK) Long-Term Debt Repayments (2009 - 2026)
Tetra Tech (TTEK) reported Long-Term Debt Repayments of $85 million for fiscal Q3 2026 (quarter ended Jun 28, 2026), down 86.9% from $650 million a year earlier and down 30.8% from the prior quarter.
Tetra Tech (TTEK) Long-Term Debt Repayments (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 28, 2026, Tetra Tech's Long-Term Debt Repayments came in at $316.03 million, down 58.0% year-over-year; for FY2025 (ended Sep 28, 2025), it came in at $771.03 million, up 168.7% from FY2024.
- Long-Term Debt Repayments has a five-year compound annual growth rate of 18.4% (FY2020 to FY2025).
- By fiscal year, Long-Term Debt Repayments came in at $287 million in FY2024 (-72.0%), $1.03 billion in FY2023 (+776.4%), $117.08 million in FY2022 (-71.7%) and $414.31 million in FY2021 (+25.1%).
- Five-year quarterly Long-Term Debt Repayments spans a low of $2.08 million in fiscal Q1 2026 and a high of $650 million in fiscal Q3 2025.
- Year over year, Long-Term Debt Repayments gained in two of the last six quarters, with growth averaging 51.7%.
- The high point for year-over-year Long-Term Debt Repayments in five years was fiscal Q4 2021 (growth of 623.9%); the low point was fiscal Q4 2022 (a decline of 96.6%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $122.92 million (Q2 2026), $2.08 million (Q1 2026) and $106.03 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 145.07 Bn | 104.35 Bn | 6.13 Bn | - |
| 2 | Cintas | 84.93 Bn | 84.01 Bn | 1.55 Bn | - |
| 3 | Iron Mountain | 33.24 Bn | 32.43 Bn | 1.07 Bn | 6.75 Bn |
| 4 | APi | 17.33 Bn | 14.36 Bn | 703.00 Mn | 302.00 Mn |
| 5 | Rollins | 15.77 Bn | 15.32 Bn | 569.95 Mn | - |
| 6 | UL Solutions | 14.77 Bn | 13.53 Bn | 417.00 Mn | 57.00 Mn |
| 7 | Aramark | 14.70 Bn | 12.64 Bn | 430.34 Mn | 11.63 Mn |
| 8 | Gartner | 13.80 Bn | 7.49 Bn | 1.19 Bn | - |
| 9 | Rentokil Initial | 10.70 Bn | 4.22 Bn | - | - |
| 10 | Tetra Tech | 8.94 Bn | 8.04 Bn | 243.21 Mn | 86.95 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 86.95 Mn |
| Mar 29, 2026 | 126.76 Mn |
| Dec 28, 2025 | 2.08 Mn |
| Sep 28, 2025 | 108.11 Mn |
| Jun 29, 2025 | 652.31 Mn |
| Mar 30, 2025 | 1.71 Mn |
| Dec 29, 2024 | 16.72 Mn |
| Sep 29, 2024 | 88.70 Mn |
| Jun 30, 2024 | 91.67 Mn |
| Mar 31, 2024 | 51.62 Mn |
| Dec 31, 2023 | 61.54 Mn |
| Oct 1, 2023 | 615.87 Mn |
| Jul 2, 2023 | 163.38 Mn |
| Apr 2, 2023 | 177.94 Mn |
| Jan 1, 2023 | 74.44 Mn |
| Oct 2, 2022 | 9.38 Mn |
| Jul 3, 2022 | 4.24 Mn |
| Apr 3, 2022 | 102.90 Mn |
| Jan 2, 2022 | 4.90 Mn |
| Oct 3, 2021 | 241.22 Mn |
Tetra Tech Long-Term Debt Repayments 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=long-term-debt-repayments&ticker=TTEK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "ticker": "TTEK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=long-term-debt-repayments&ticker=TTEK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();