Distinguished Architect, Data Platform

🕒 March 25

🏄 California – Remote

🏄 California – Remote

💵 $275k - $330k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

CloudZero

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2017

☁️ SaaS

🤖 Artificial Intelligence

💸 Finance

💰 Series A on 2021-03

SaaS • Artificial Intelligence • Finance

CloudZero is a leading cloud cost optimization platform that empowers businesses to manage and reduce their cloud expenses efficiently. With advanced features like AI-driven anomaly detection, detailed cost allocation without perfect tags, and comprehensive Kubernetes visibility, CloudZero provides a single pane of glass for viewing and analyzing cloud expenditures from any infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), or software-as-a-service (SaaS) provider. The platform offers tools for budgeting, forecasting, and maximizing discounts while promoting accountability and cost-conscious engineering. CloudZero strives to enable companies to achieve financial control and predictability in cloud spending, optimizing their cloud infrastructure for better profitability.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• Offers Equity • Offers Bonus