Summary
Join a lean engineering team responsible for scaling the backbone of a massive real-time data platform. You will design cloud infrastructure, build and harden large-scale batch and incremental pipelines, tune high-volume databases, and establish strong DevOps practices. This is a high-ownership opportunity for an infrastructure engineer who enjoys solving reliability, latency, throughput, and cost challenges at terabyte scale.
Highlights
Own and scale infrastructure for a high-volume data platform handling tens to hundreds of terabytes. The role offers broad technical ownership across cloud architecture, data pipelines, databases, reliability, performance, and cost optimization in a small, highly autonomous engineering environment.
Description
DataMoon is an audience, intent, and enrichment platform.
We give marketing and RevOps teams the same data and tooling that historically lived behind a six-month enterprise procurement cycle — over plain HTTP, with a dashboard you can hand to a new hire.
Under the hood, that means operating a large-scale identity graph and moving serious volume: we're scaling from tens into hundreds of terabytes of data, served in real-time and at scale.
If you like infrastructure problems where reliability, latency, and cost all actually matter, this is that job.
About the Role
We're looking for a systems/infrastructure engineer to own and scale the backbone of our data platform — from batch and incremental pipelines to the databases and cloud infrastructure they run on.
You'll partner closely with our engineering team to scale our data to the moon, leading the infrastructure and pipeline reliability side.
What You'll Do
Design, build, and harden data pipelines that scale into the hundreds of terabytesOwn infrastructure architecture across AWS (compute, storage, networking, IAM)Build and maintain batch and incremental data processing workflowsManage and tune our databases: PostgreSQL and ClickHouse at scaleEstablish solid DevOps practices — CI/CD, observability, monitoring, and deployment automationDrive reliability, throughput, and cost-efficiency across storage-heavy, high-volume, real-time workloads
What We're Looking For
Strong infrastructure and systems engineering backgroundHands-on AWS experience (EMR, Glue, S3, EC2, or similar)Experience developing and scaling data pipelines at large data volumeTrack record operating in the tens-to-hundreds-of-terabytes rangeDatabase experience with PostgreSQL required; ClickHouse a strong plusDevOps fluency: infrastructure-as-code, CI/CD, containerization, monitoringComfort operating independently and dividing ownership on a small team
Nice to Have
Laravel Cloud / Laravel Forge experienceFamiliarity with data activation / reverse-ETL tools (Fivetran, Polytomic)Experience with identity resolution or audience data systemsSpark / distributed processing experience
