Distinguished Engineer, Data Platform

About the Role

CloudZero is growing fast. Our customer base is expanding, the data challenges we're solving are getting more complex, and the platform is scaling to match. As a Distinguished Engineer on the Data Engineering team, you'll own some of the hardest infrastructure problems at CloudZero: shaping the next-generation streaming data platform, the dimensional cost model underlying every attribution decision, the hot/cold storage architecture serving both real-time and historical queries, and the query engine that powers our entire product.

This is real platform architecture work at real scale, not a consulting role or a review-and-advise job. You'll define the roadmap, drive the foundational decisions, and be a force multiplier for a talented engineering team — evolving CloudZero from batch-oriented pipelines toward a streaming-first architecture where cost attribution reaches engineers within seconds of a resource being used, not the next morning.

This role is ideal for an architect who has built systems like this before, has the scars to prove it, and wants to see their decisions matter in direct and measurable ways for customers and for the business.

What You'll Do

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

Drive Streaming Infrastructure to Production

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

Tackle the Dimension Cardinality Problem

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

Evolve the Query Layer

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

Extend Cost Attribution to Real-Time

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

Shape the Data Engineering Roadmap

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

Elevate the Engineering Team

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

What You Bring

Data Platform & Architecture

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

Data Modeling & Dimensional Design

Expert in dimensional data modeling including fact/dimension schema design, slowly changing dimensions, and cardinality management

Deep understanding of the materialization tradeoff space: full vs. incremental, push vs. pull, pre-aggregate vs. query-time

Experience with cost attribution, showback/chargeback, or multi-tenant data partitioning patterns

Strong SQL and query optimization background across predicate pushdown, partition pruning, and cost-based query planning

Query Engines & Compute

Hands-on with distributed query engines such as Trino, Presto, Spark SQL, or DuckDB including configuration, optimization, and production operations

Understands catalog and metadata management and how it couples to query engines

Comfortable with cloud data warehouses such as Snowflake, BigQuery, and Redshift and how they integrate with open table formats

Experience driving query engine migrations while maintaining production SLAs

Engineering Leadership

Track record as a technical anchor for a data platform or data engineering team

Writes clear ADRs, RFCs, and technical design docs that bring engineers along

Can drive multi-month, multi-team technical initiatives from inception to production without heavy process overhead

Communicates complex tradeoffs to non-technical stakeholders including product and business leadership

Comfortable in a high-autonomy environment: builds consensus, influences through expertise, and helps teams move forward

Bonus If You Have...

FinOps or cloud cost domain experience

Multi-cloud data ingestion across AWS, Azure, and GCP

Apache Flink at production scale

Lakehouse architecture patterns

Real-time feature engineering for ML

Data mesh or domain-oriented design patterns

Prior startup or high-growth SaaS experience

Open source contributions to the data ecosystem

About CloudZero

Cloud cost management is one of the biggest challenges organizations face today. As cloud adoption continues to accelerate, so do the complexities and costs associated with it, and macroeconomic conditions only increase pressure to prove cloud efficiency.

CloudZero is a SaaS platform at the intersection of next-generation cloud cost management and FinOps. We ingest billing and usage data from all cloud, SaaS, and PaaS providers, organize it in real time according to our customers' business structures, and empower organizations to make more informed business decisions.

Since our founding in 2016, our mission has been to make efficient innovation a reality for every cloud-driven organization. We believe every engineering decision is a buying decision, and we're applying proven reliability engineering principles to financial efficiency.

We believe the best AI empowers users with clear insights and confident decisions, transforming complex cloud cost data into actionable intelligence that drives meaningful business outcomes.

To date, we've raised over $56 million from leading venture capital firms. We're solving problems of massive scale, business importance, and complexity in a space that needs it more than ever.

Compensation Range: $275K - $330K