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Principal data platform architect (spark / big data / distributed systems)

Daivio
Architecte
Publiée le Publiée il y a 6 h
Description de l'offre

We’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 Role

We 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 Do

* Architect and build large-scale data processing systems
* Design and optimize Apache Spark workloads (batch + streaming)
* Own the architecture for:
* transformation
* storage
* query layers
* Optimize for:
* throughput
* cost
* Design distributed systems that don’t fall apart at scale
* Work closely with AI/ML layers to enable intelligent data interaction


What We’re Looking For

We 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 datasets
* compute vs storage
* latency vs cost
* Thinks in systems, not tools
* Has strong opinions about data architecture patterns
* Can operate with high ownership and zero hand‑holding


Tech Stack (Current & Evolving)

* Apache Spark (core component)
* Distributed data processing (batch + streaming)
* Data lakes / lakehouse architectures
* Python / Scala
* Kubernetes‑based execution environments


Why This Role is Different

* You are not plugging into an existing system — you are defining it
* You will shape how AI interacts with data at scale
* You will solve non‑trivial distributed systems problems daily
* You will work directly with founders on core architecture


What We Offer

* Real technical influence
* The chance to build a category‑defining data platform


Who This Is NOT For

* People who only used Spark via notebooks
* People without production‑scale experience
* People who optimize for comfort over impact


How to Apply


Send:

* LinkedIn / CV
* Short 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.

#J-18808-Ljbffr

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