Distinguished Architect, Data Platform

🕒 vor 3 Monaten

🏄 California – Remote

🏄 California – Remote

💵 $275.000 - $330.000 / Jahr

⏰ Vollzeit

🟠 Senior

🔴 Experte

🚰 Dateningenieur

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CloudZero

WebsiteLinkedInAlle Stellen

11 - 50 Mitarbeiter

Gegründet 2017

☁️ SaaS

🤖 Künstliche Intelligenz

💸 Finanzen

💰 Series A im 2021-03

SaaS • Artificial Intelligence • Finance

CloudZero ist eine führende Plattform zur Optimierung von Cloud-Kosten, die Unternehmen in die Lage versetzt, ihre Cloud-Ausgaben effizient zu verwalten und zu reduzieren. Mit fortschrittlichen Funktionen wie KI-gesteuerter Anomalieerkennung, detaillierter Kostenallokation ohne perfekte Tags und umfassender Kubernetes-Transparenz bietet CloudZero eine zentrale Übersicht zur Ansicht und Analyse von Cloud-Ausgaben von jedem Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) oder Software-as-a-Service (SaaS) Anbieter. Die Plattform bietet Werkzeuge für Budgetierung, Prognosen und die Maximierung von Rabatten, während sie Verantwortlichkeit und kostenbewusstes Engineering fördert. CloudZero strebt danach, Unternehmen zu befähigen, finanzielle Kontrolle und Vorhersehbarkeit bei Cloud-Ausgaben zu erreichen und ihre Cloud-Infrastruktur für eine bessere Rentabilität zu optimieren.

Beschreibung

• Define the Data Platform Architecture • Lead end-to-end technical design for CloudZero's next-generation data platform, from event ingestion and stream processing through hot/cold storage and the query layer to the API surface • Document architectural decisions, tradeoffs, and migration strategies with the rigor of an RFC-driven process • Shape and drive every layer of the new architecture: event ingestion, stream processing and enrichment, real-time serving, analytical storage, query layer, and API • Design and deliver CloudZero's real-time data pipeline from ingestion through enrichment to serving • Establish SLOs for throughput, latency, and correctness, and build the operational playbooks that make this system trustworthy enough to replace the batch pipelines our entire product currently depends on • Tackle real-time streaming at scale across thousands of customers simultaneously, with fault tolerance, backpressure awareness, and correctness as non-negotiables • Redesign CloudZero's dimensional cost model to support high-cardinality, multi-dimensional cost attribution without runaway materialization costs • Drive incremental, delta-based materialization strategies using modern open table formats, dramatically reducing expensive full-rebuild jobs and unlocking millions in annual infrastructure savings • Assess CloudZero's current query infrastructure, drive in-flight migrations to completion, and lead the evolution of the query engine layer going forward • Own performance optimization across partition pruning, predicate pushdown, and query planning, and set the vision for how the query layer grows as data volumes scale 10x • Evolve CloudZero's proprietary cost attribution engine from a batch-oriented model to one that assigns complex cost dimensions by team, feature, and customer within seconds of resource usage • Rethink enrichment, data lineage, and correctness guarantees in a streaming context • Partner with product, infrastructure, and analytics engineering to define a multi-year data platform roadmap • Build consensus across engineering leadership on foundational investments including table formats, streaming frameworks, query engines, and schema management • Participate in architecture reviews, contribute to design patterns and best practices, and mentor senior and staff engineers through code review, pairing, and structured feedback • Make everyone around you better, not by directing, but by raising the collective craft

🎯 Anforderungen

• 10+ years in data engineering with a clear trajectory toward principal or staff-level architecture • Built and operated large-scale data platforms serving tens of millions of events per day in production • Deep experience with streaming systems such as Kafka, Kinesis, Flink, or Spark Streaming at real production throughput • Strong hands-on fluency with modern open table formats including Apache Iceberg, Delta Lake, and Hudi, including compaction, partitioning strategy, and time-travel queries • Designed hot/cold storage architectures with explicit latency SLOs per tier • Proven ability to drive a data platform end to end, not just a single layer

🏖️ Vorteile

• Offers Equity • Offers Bonus