Location: RemoteCompany: DaivioLevel: Staff / Principal / ArchitectAbout UsWe’re building Daivio — an AI-native data platform where users can interact with their data like they interact with AI.We are tackling a hard problem:Making large-scale data processing intuitive, fast, and intelligent.This means solving serious distributed systems challenges.The RoleWe are looking for a world-class Data Architect / Engineer who has built and scaled real big data systems.This is not about dashboards.This is about designing the engine behind them.You will define how data flows, scales, and performs inside Daivio.What You’ll DoArchitect and build large-scale data processing systemsDesign and optimize Apache Spark workloads (batch + streaming)Own the architecture for:data ingestiontransformationstoragequery layersBuild high-performance data pipelines handling large volumesOptimize for:latencythroughputcostDesign distributed systems that don’t fall apart at scaleWork closely with AI/ML layers to enable intelligent data interactionMake foundational architecture decisionsWhat We’re Looking ForWe are looking for someone who:Has deep, hands-on Apache Spark expertise (not just usage – internals matter)Understands distributed systems fundamentals (partitioning, shuffling, fault tolerance)Has built or scaled data platforms handling large datasetsKnows trade-offs between:batch vs streamingcompute vs storagelatency vs costThinks in systems, not toolsHas strong opinions about data architecture patternsCan operate with high ownership and zero hand-holdingTech Stack (Current & Evolving)Apache Spark (core component)Distributed data processing (batch + streaming)Data lakes / lakehouse architecturesPython / ScalaCloud (Azure preferred)Kubernetes-based execution environmentsWhy This Role is DifferentYou are not plugging into an existing system — you are defining itYou will shape how AI interacts with data at scaleYou will solve non-trivial distributed systems problems dailyYou will work directly with founders on core architectureWhat We OfferHigh ownership, zero bureaucracyReal technical influenceThe chance to build a category-defining data platformWho This Is NOT ForPeople who only used Spark via notebooksPeople without production-scale experiencePeople who optimize for comfort over impactHow to ApplySend:LinkedIn / CVShort note: What is the hardest data system you’ve built and why?We’re building for scale from day one. If you’ve done it before, we want to talk.