01 The fastest movers aren't the biggest names.
Scope = current employees at 30 leading fintech companies whose job function is “Engineering & Technology” (excluding interns and incoming hires), global scope, 25,860 people in total. All figures are aggregate statistics; the report shows no personal information.
The fastest movers aren't the biggest names. At Ramp, engineers who joined in the past year make up 32.9%, nearly 4x its peer Brex (8.9%); Airwallex (29.3%) and Monzo (24.6%) follow close behind. At the other end, hiring is all but frozen at Klarna (7.1%) and Cash App (4.2%).
In peer-to-peer talent flow, Ramp runs away with it (net +51), while Stripe is the highest-throughput “central exchange” (102 in, 77 out, net +25); the biggest net donors are Nubank, Robinhood, and Klarna. The thickest pipe:Stripe → Ramp, 21 engineers.
The US cohort is fed by Big Tech — at Plaid (45.5%) and Stripe (42.1%), nearly half of engineers come from FAANG-tier companies; the European / LatAm cohort relies on regional tech firms and IT outsourcing (Revolut ← EPAM, Yandex; Nubank ← Itaú, PicPay, CI&T). The single biggest “academy” feeding the entire sector is Amazon, not a bank.
Among these companies' alumni, 3,829 have already become their own boss, but only 19% went back into fintech — the talent is spilling over into the broader startup economy. On per-capita founder-minting density, Ripple (49 per thousand), Brex (41 per thousand), and Wealthfront (38 per thousand) lead.
02Hiring momentum leaderboard: who's accelerating, who's hitting the brakes
The most direct gauge of momentum is “what share of current engineers joined in the past 12 months.” The sector-wide average is 16.9% (about 1 in 6). Sorted, the spread is striking: at the fastest, Ramp, a third of engineers joined this past year, while the slowest few are nearly frozen. Median tenure tells the same story — just 15 months at Ramp, versus over 45 months at Cash App and Varo.
03Net inflow / bleeding leaderboard: the winners and losers of intra-cohort talent flow
Isolating the flows between the 30 companies: if someone is now at A and previously worked at peer B, we record one B→A. We measure who wins net within the cohort as “people pulled from peers − people lost to peers.” This is adirectional signal — it counts only intra-cohort moves, not total hiring; the absolute numbers run small, so focus on the ranking and direction.
Net importers · cohort winners
Net donors · bleeding talent
The thickest talent pipes (count of current staff who came from that peer): Stripe is both the biggest outflow and the biggest inflow — the sector's talent clearinghouse; meanwhile Robinhood acts like a training camp, steadily feeding engineers to Coinbase, Ramp, and Stripe.
| Source company | Destination company | Flow size | |
|---|---|---|---|
| Stripe | → | Ramp | 21 engineers |
| Coinbase | → | Stripe | 18 engineers |
| Robinhood | → | Coinbase | 13 engineers |
| Robinhood | → | Ramp | 11 engineers |
| Nubank | → | Brex | 10 engineers |
| Klarna | → | Stripe | 9 engineers |
| Stripe | → | Plaid | 8 engineers |
| Coinbase | → | Robinhood | 8 engineers |
| Stripe | → | Coinbase | 7 engineers |
| Robinhood | → | Stripe | 7 engineers |
| Wise | → | Stripe | 6 engineers |
| Wise | → | Monzo | 6 engineers |
04Two fintech worlds: Big Tech-bred vs regionally bred
“Where engineers come from” splits these 30 companies cleanly in two. The chart below shows each company's share of engineers with US Big Tech (FAANG-tier) experience — uniformly high at US companies, uniformly low at European / LatAm ones. But low doesn't mean “no pedigree”; it means they hire from a different talent pool.
The top “academy” feeding the entire sector
| Source | Type | Engineers exported | Share of sector |
|---|---|---|---|
| Amazon | US Big Tech | 1,880 | 7.3% |
| Microsoft | US Big Tech | 849 | 3.3% |
| US Big Tech | 768 | 3.0% | |
| Meta | US Big Tech | 638 | 2.5% |
| IBM | US Big Tech | 487 | 1.9% |
| Accenture | IT / outsourcing / other | 366 | 1.4% |
| Capital One | Traditional finance | 278 | 1.1% |
| JPMorgan | Traditional finance | 271 | 1.0% |
| Apple | US Big Tech | 256 | 1.0% |
| Oracle | US Big Tech | 255 | 1.0% |
| Uber | US Big Tech | 254 | 1.0% |
| Goldman Sachs | Traditional finance | 250 | 1.0% |
| Itaú | Traditional finance | 223 | 0.9% |
| TCS | IT / outsourcing / other | 221 | 0.9% |
| PayPal | Traditional finance | 213 | 0.8% |
Where the regional cohort actually hires from
The real backbone sources for European / LatAm companies are regional tech firms and IT outsourcing, not FAANG:
| Company | Home base | Top four sources (count) |
|---|---|---|
| Revolut | Europe | EPAM Systems (100), Yandex (64), Sberbank (46), Luxoft (35) |
| Klarna | Europe | Ericsson (39), Accenture (38), Netlight (24), IBM (23) |
| N26 | Europe | IBM (11), Accenture (10), eDreams ODIGEO (9), everis (9) |
| Nubank | LatAm | Itaú (201), PicPay (119), CI&T (94), IBM (81) |
| Wise | UK | Amazon (28), EPAM Systems (24), Morgan Stanley (21), Ericsson (20) |
| Checkout.com | UK | Accenture (16), Orange Business Services (14), Microsoft (13), Icefire (12) |
| Adyen | Europe | Amazon (36), ING (23), Google (22), IBM (20) |
| Airwallex | APAC | Shopee (30), TikTok (23), ByteDance (21), Grab (15) |
05Founder spillover: who is the “founder cradle,” and where they went
Zooming out to alumni: these 30 companies have produced 3,829 founder / CEO seats in total (counted separately for those who served at multiple firms). The key question is “where did they go” — only 19% went on to found another fintech, while the remaining four-fifths took their experience into the broader startup economy. On per-capita density, alumni of crypto and first-generation unicorns are the keenest founders.
06The 30-company side-by-side table
Every dimension in one table. “Engineer share” = engineers as a share of total headcount (size ≠ engineering depth: Kraken hits 60.6%, Revolut just 11.0%); “joined in the past year” = hiring momentum; “net intra-cohort flow” = net peer flow; “Big Tech background” = share with FAANG-tier experience; “founders per thousand” = founder-spillover density.
| Company | Category | Engineers | Engineer share | Joined in the past year | Net intra-cohort flow | Big Tech background | Founders per thousand | Home base |
|---|---|---|---|---|---|---|---|---|
| Stripe | Payments & money infrastructure | 3,689 | 34.8% | 18.1% | +25 | 42.1% | 21.1 | US |
| Nubank | Neobanks & consumer finance | 3,242 | 33.6% | 20.9% | −29 | 5.5% | 11.1 | LatAm |
| Coinbase | Crypto & digital assets | 1,870 | 33.2% | 23.1% | −10 | 33.7% | 34.0 | US |
| Revolut | Neobanks & consumer finance | 1,616 | 11.0% | 14.4% | −1 | 4.0% | 15.0 | Europe |
| Klarna | Credit & buy-now-pay-later | 1,310 | 37.2% | 7.1% | −21 | 4.5% | 29.7 | Europe |
| Adyen | Payments & money infrastructure | 1,288 | 30.7% | 11.2% | +6 | 9.5% | 15.7 | Europe |
| Toast | Payments & money infrastructure | 1,276 | 21.0% | 16.5% | 0 | 13.0% | 9.6 | US |
| SoFi | Credit & buy-now-pay-later | 1,013 | 25.2% | 18.3% | +11 | 30.3% | 15.9 | US |
| Kraken | Crypto & digital assets | 965 | 60.6% | 19.5% | +3 | 3.8% | 3.2 | UK |
| Robinhood | Investing & wealth management | 962 | 29.2% | 19.6% | −25 | 38.8% | 22.0 | US |
| Wise | Payments & money infrastructure | 951 | 14.0% | 21.3% | +11 | 8.5% | 15.4 | UK |
| Affirm | Credit & buy-now-pay-later | 941 | 38.1% | 14.2% | −12 | 21.7% | 27.4 | US |
| Monzo | Neobanks & consumer finance | 669 | 19.0% | 24.6% | +13 | 16.3% | 16.2 | UK |
| Cash App | Neobanks & consumer finance | 661 | 24.4% | 4.2% | 0 | 31.2% | 18.3 | US |
| BILL | Corporate spend & B2B finance | 566 | 25.4% | 6.6% | −3 | 10.4% | 13.0 | US |
| Checkout.com | Payments & money infrastructure | 524 | 28.0% | 10.5% | −6 | 5.7% | 20.8 | UK |
| Chime | Neobanks & consumer finance | 508 | 28.2% | 9.0% | +13 | 31.7% | 21.9 | US |
| N26 | Neobanks & consumer finance | 505 | 33.1% | 11.4% | −16 | 4.6% | 36.3 | Europe |
| Upstart | Credit & buy-now-pay-later | 458 | 29.9% | 18.2% | +1 | 20.5% | 16.0 | US |
| Ramp | Corporate spend & B2B finance | 382 | 23.4% | 32.9% | +51 | 31.7% | 22.9 | US |
| Brex | Corporate spend & B2B finance | 353 | 24.7% | 8.9% | −3 | 30.0% | 40.8 | US |
| Plaid | Payments & money infrastructure | 341 | 30.6% | 20.9% | +16 | 45.5% | 30.1 | US |
| Ripple | Crypto & digital assets | 329 | 29.9% | 20.1% | −8 | 24.0% | 49.1 | US |
| Marqeta | Payments & money infrastructure | 306 | 39.6% | 8.9% | −10 | 20.9% | 22.6 | US |
| Airwallex | Payments & money infrastructure | 281 | 19.2% | 29.3% | +10 | 18.1% | 19.7 | APAC |
| Lemonade | Insurtech | 241 | 21.9% | 13.9% | +2 | 8.3% | 17.8 | Other |
| Rapyd | Payments & money infrastructure | 196 | 29.6% | 15.3% | −3 | 1.5% | 15.7 | Other |
| Wealthfront | Investing & wealth management | 181 | 49.6% | 18.5% | −6 | 25.4% | 38.2 | US |
| Betterment | Investing & wealth management | 170 | 30.0% | 18.5% | −9 | 11.2% | 36.1 | US |
| Varo Bank | Neobanks & consumer finance | 66 | 17.3% | 1.6% | 0 | 12.1% | 16.3 | US |
Questions this report answers
- How many current fintech engineers are in the 2026 momentum sample?
- 30 fintech leaders, 25,860 current engineers: who net-imports talent, who bleeds it, where the biggest talent pipe runs, and where founders spill over — momentum / talent flow / sources / founder factory.
- Which fintech is the top net importer of engineers inside this 30-company cohort?
- In peer-to-peer talent flow, Ramp runs away with it (net +51), while Stripe is the highest-throughput “central exchange” (102 in, 77 out, net +25); the biggest net donors are Nubank, Robinhood, and Klarna.
- Who is in the 25,860-person Engineering & Technology scope?
- Scope = current employees at 30 leading fintech companies whose job function is “Engineering & Technology” (excluding interns and incoming hires), global scope, 25,860 people in total. All figures are aggregate statistics; the report shows no personal information.
- How should this report be cited?
- Metix AI Talent Intelligence, 2026-06-24. FinTech Engineering Talent Momentum Leaderboard 2026 | Metix AI. https://metix.ai/reports/mapping/fintech-talent-momentum-2026
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