Dataprana

At Dataprana, we're building something exceptional — and that means bringing in exceptional people. We're thrilled to announce that we're hiring across several key teams, with roles spanning leadership, strategy, finance, and talent. If you're ready to make an impact at a company where your work truly matters, we'd love to hear from you. 🔗 Open Positions: 🟢 SVP Power → https://lnkd.in/gv-33Ptx 🟢 VP Strategic Partnerships → https://lnkd.in/g8xxqWb3 🟢 Talent Acquisition Manager → https://lnkd.in/gZnCPUmP 🟢 Chief Financial Officer → https://lnkd.in/eKpVZPQ7 These are pivotal roles that will shape the future of Dataprana. We're looking for leaders and builders who are driven, collaborative, and ready to grow with us. 🔁 Know someone who would be a great fit? Tag them below or share this post — it could be the opportunity they've been waiting for. #Hiring #OpenRoles #JoinOurTeam

🚀 We're Hiring: Chief Financial Officer (CFO) Dataprana is on a mission to build 5 GW of AI/HPC data center capacity by 2030 — and we're looking for an exceptional financial leader to help us get there. As CFO, you will serve as a key member of our Executive Team, owning financial strategy, capital formation, and investor relations across Dataprana and its subsidiaries. This is a high-impact, high-visibility role for a seasoned builder who thrives in fast-moving, infrastructure-heavy environments. What you'll lead: • Ongoing fundraising efforts • Structuring of project finance solutions across a broad infrastructure pipeline • Design and implementation of financial systems across multiple entities and project SPVs • Investor relations, fund management, treasury strategy, and regulatory compliance • Building and scaling a high-performing finance team Ideal candidates bring: ✔ 10+ years of progressive financial leadership experience ✔ Proven track record raising $100M+ in capital ✔ Deep expertise in AI/HPC infrastructure, data centers, energy, or digital assets ✔ Experience in fund formation, project finance, and complex capital structures ✔ A builder's mindset and the ability to operate with speed and ownership 📍Based in Miami, FL | Hybrid or On-Site Preferred | Remote Considered for Exceptional Fit If you're ready to help build something transformational, we want to meet you. 🔗 Apply here: https://lnkd.in/eKpVZPQ7 #CFO #ExecutiveHiring #FinanceLeadership #Hiring

Land. Power. Permits. At Dataprana, our team is building out a pipeline of over 400 MW worth of energized land parcels. If you’re looking to launch your next AI development, we may have the site for you. Online in 12-18 months. Let us know what you’re looking for — info@dataprana.io. 🌐 Visit dataprana.io to learn more about our land & energy division.

We started as a Bitcoin mining company. Now we’re building infrastructure for AI. That shift has made one thing clear: AI is now scaling at the speed of power, not compute. Bringing new capacity online still means navigating land ⛰, permitting 📄, and grid interconnection timelines 🏗 that can stretch for years. For today’s increasing AI compute demand, that simply isn’t viable. That’s why we focus on mid-scale deployments. Instead of waiting years for a single hyperscale campus, 10–50MW projects allow us to move faster, deploy incrementally, and bring capacity online sooner. It’s also why GPUaaS providers are increasingly working with Bitcoin-native operators. We’ve spent years solving for power, uptime, and deployment under real constraints. That experience carries directly into how we approach AI infrastructure. At Dataprana, this approach underpins our ~500MW pipeline across North America. In this environment, the advantage goes to those who can secure powered land and bring compute online first. To learn more, head to dataprana.io or reach out to us directly: info@dataprana.io.

Jensen Huang was here ✍️ The Dataprana Energy team is on the ground in San Jose this week for NVIDIA GTC 2026! 🤝 We’ve been connecting with developers, operators, and partners across the AI and data center space, and the momentum is clear. Demand for compute is accelerating, while infrastructure is racing to keep up. ⚡️ Across conversations, one theme continues to stand out: powered land + speed to power is now the critical constraint. It’s been great spending time in person with the teams building this next era of the industry. If you’re here, we’d love to connect. 🔗 Meet with us: https://lnkd.in/gYqgQ8NA #NVIDIAGTC #AIFactory #AIInfrastructure #Dataprana

NVIDIA GTC is just 3 days away ⏳ If you’re looking to chat about land, power, the future of AI data centers or just want to meet in person, let’s connect. 🗓 Reach out to our Energy team or book a meeting in advance: https://lnkd.in/gYqgQ8NA We look forward to meeting with other industry innovators in San Jose. #NVIDIAGTC Arseniy Grusha Igor Kovalyshkin Kristina Karupovic

Everyone is talking about gigawatt AI campuses. But no one is talking about the immediate compute needs that may actually be fulfilled by smaller, 10-50 MW clusters. Much of the industry conversation has focused on the largest AI hyperscale builds. And while those projects are critical, they often require multi-year development timelines and massive grid upgrades. At the same time, AI demand and adoption is accelerating right now. From copilots and generative search to enterprise AI platforms, the rapid growth of real-world AI applications is creating immediate demand for edge compute data centers — this is the infrastructure that processes localized AI user queries as users interact with it. This is exactly where small to mid-scale AI data centers are gaining momentum. These smaller clusters offer several advantages: ⚡ Faster speed-to-market Utilities can often deliver power at this scale sooner than gigawatt deployments. ⚡️ Utiliizing existing infrastructure Most projects of this size don’t require new grid infrastructure to be built. ⚡ Phased infrastructure buildouts Great for modular infrastructure that can accommodate on-demand expansion. ⚡ Localized proximity to metro population areas Supporting distributed edge compute workloads across multiple regions. As a result, many AI infrastructure developers are increasingly prioritizing a power-first strategy — identifying sites that can be powered by existing grid infrastructure. The next generation of AI infrastructure won’t be centered on core, hyperscale data centers — instead, it will utilize a nodal approach by clustering smaller deployments which serve as a link between the core data center and the end user. 🌐 Want to build with us? Get in touch today to learn more about our energized site portfolio.

Bitcoin had a slow year. If you bought BTC in January 2025 and held it through the year, you waded through months of price stagnation and still ended down ~2.2%. For many, this reinforced the familiar narrative that when Bitcoin struggles, everything built atop it must be struggling too. But that wasn’t entirely true. Bitcoin mining saw business as usual. Here’s why: 📈 Spot Bitcoin is dominated by price.  If BTC goes up, you win. If it doesn’t, you either wait or sell for a loss. ⛏️ Mining isn’t a direct price bet. It’s a revenue-generating infrastructure business shaped by protocol rules, network competition, operating efficiency, energy costs, and tax treatment. When prices rise, revenue is worth more. When prices stall, the network’s activity doesn’t stop. 📖 Read the full breakdown: https://lnkd.in/g__CJzb5 If you’re exploring mining exposure and want to see what these economics look like with real power pricing, real hardware, and a clean operating model, Dataprana can walk you through it → visit https://lnkd.in/g7xxFEjN or get in touch today info@dataprana.io 📩

Our Prana Energy team is headed to NVIDIA GTC in San Jose from March 16-19. We have over 400 MW of small to mid-scale energized parcels and are looking to partner with off-takers and developers. Let's connect. Going to NVIDIA GTC? Schedule a time to meet with us: 🔗 https://lnkd.in/eX38gS4K // Arseniy Grusha, Igor Kovalyshkin, Kristina Karupovic

The real constraint in AI right now? Power infrastructure. Access to power and grid interconnection timelines are becoming just as critical as GPUs. Demand for compute is accelerating, but typical hyperscale data centers often take years to develop and require billions in upfront capital. Between land aggregation, permitting, transmission upgrades, and grid interconnection timelines, bringing large-scale facilities online has become a long and complex process. That model works for hyperscalers with large balance sheets, but it doesn’t work for most developers and operators that need capacity much sooner. This is where mid-scale and modular data center development is gaining traction. Building hyperscale campuses requires significant time, capital, and power infrastructure. By contrast, 10–50 MW deployments can move much faster, often leveraging existing grid capacity and available infrastructure to reach market sooner. Capacity can also be deployed incrementally across smaller sites and land parcels, allowing operators to scale alongside demand rather than committing to multi-year build outs. This approach offers multiple advantages:  ⌛️ Faster speed-to-market  📉 Lower upfront capital requirements  🏗 Flexible, incremental scaling  🔋 Greater proximity to both available power and end-users As demand for compute continues to grow, the industry will move toward a mix of hyperscale campuses and smaller, purpose-built deployments. The real competitive advantage isn't building the biggest data center, but bringing compute online as quickly as possible and avoiding multi-year wait times and delays. 🏆 This shift is one reason Dataprana focuses on mid-scale, power-first deployments in the 10–50 MW range. Smaller projects tend to interconnect faster, energize sooner, and reach revenue generation far earlier than hyperscale developments. We see a future where speed to power becomes one of the most important advantages in compute infrastructure. And it's already here. 📩 To learn more, head to dataprana.io or get in touch with us at info@dataprana.io.