2024 · Prelaunch

Data Galaxy Foundation

Built the identity, deployment, and analytics foundation for a prelaunch cloud service connecting existing on-premises installations.

Tech stack: AWS · Python · Django · Keycloak · OAuth2/OIDC · Apache Airflow · PostgreSQL · Elasticsearch · Docker · Ansible · Looker Studio
Operating context: Prelaunch cloud foundation · Fixed four-month delivery window · Development, staging, and production-oriented paths
Role: Software Engineer, first engineer on the new cloud-product team
Ownership: The authenticated Django service boundary, cloud environments and deployment automation, and an end-to-end tenant-scoped analytics proof of concept.

Selected ownership

Authenticated cloud API

Established a Keycloak-backed Django service boundary for installation identities and tenant-scoped metric queries.

AWS environments and repeatable deployment

Established repeatable release paths across AWS-hosted cloud services and connected installation environments using Docker, Ansible, environment inventories, and a container registry.

Deployment allocationdevelopment · staging · production-oriented

Build and releasesource · CI jobs

Container registryversioned service images

Deployment controlAnsible · Docker Compose

AWS-hosted cloud servicesWeb portal · identity · cloud APIenvironment-specific service configuration

Analytics proof of conceptElasticsearch · Airflow · PostgreSQLcontainerized supporting services

Connected installationsOn-premises environmentsexisting product · automated deployment target

Tenant-scoped analytics proof of concept

Validated an end-to-end path from behavior logs and identity data to embedded, tenant-isolated BI without requiring customer Google accounts or moving metrics into BigQuery.

The cloud service was prelaunch when I left. Existing on-premises installations appear only as product context. This record does not claim production traffic, adoption, uptime, or customer outcomes.