Staff Software Engineer, Data
Stability AI · Remote
About this role
**Staff Software Engineer — Data** ## The Team The Data team builds and runs the systems that make Stability AI’s data usable—both to operate the business and to train our models. We’re a small, collaborative team working closely with Finance, Marketing, SRE, Security, Product, and Research. We focus on outcomes rather than hours, with deep technical access and freedom to build. **Our stack:** AWS (S3, Athena, Glue, EMR, Step Functions, EventBridge), Iceberg, dbt, Postgres, Terraform, Helm, GitHub Actions, QuickSight, Stripe, Auth0, HubSpot, Customer.io, PostHog, OpenTelemetry, SLURM (or similar). We care about judgement more than the logo. ## The Work You’ll own the company data platform end to end: the AWS data lake, the transformation layer, integrations between business systems, and the Kubernetes-based infrastructure that runs them. Business-critical data (billing, usage telemetry, identity, CRM, ERP, cloud cost) lives across many systems—your job is to connect them and keep everything reliable. You’ll also be the data engineer for our research teams across audio, video, image, and 3D—building pipelines that turn raw media into training-ready datasets. This is a hands-on role with real ownership (not a data-prep or analyst seat). ### Responsibilities - **Own** the company data platform end to end: S3/Athena/Glue lake, dbt project and daily builds, ingestion from Stripe, Auth0, HubSpot, OpenTelemetry, and product events, plus the Postgres serving layer for dashboards and AI agents. - **Build and operate** integrations between billing, CRM, ERP, identity, and telemetry so revenue, usage, cost, and customer identity reconcile automatically (not via spreadsheets/tickets). - **Design and maintain** the warehouse layer: dimensional models, data contracts with product engineering for event schemas, quality tests, lineage, and a catalog. - **Enforce** PII tiering (open vs. restricted schemas) through access grants, working with Security and Legal. - **Process data at scale:** billions of telemetry rows, terabyte log streams, Iceberg tables, partitioning, and cost control. - **Own orchestration and infrastructure:** orchestration on EKS, Helm, Terraform, CI/CD, monitoring/alerting, and join the business-hours on-call rotation for daily pipelines. - **Deliver operational reporting** for Finance and leadership (e.g., revenue by business line, credits/prepaid liability, cloud cost by department). - **Support research teams** across every modality: source, license-check, ingest, and version large training datasets for audio, video, image, and 3D. - **Build pipelines** for generation, filtering, deduplication, and captioning to turn raw/synthetic media into training-ready shards; run at scale on SLURM and cloud object storage. - **Keep lineage, quality metrics, and dataset documentation** current so researchers can reproduce training sets. - **Lead design reviews, mentor teammates,** and write runbooks to remove single-person dependencies. - **Partner** with Finance, Marketing, SRE, Security, Product, and Research on company-wide data initiatives. ## What You Bring You’re an engineer with strong software engineering habits and deep warehouse modelling experience—plus the judgement to understand what a metric means (and what it doesn’t). ### Experience - 6+ years building and running production data platforms, including ownership of the architecture. - Experience integrating SaaS business systems (Stripe, HubSpot, an ERP, an identity provi
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