AI-Driven Senior Support Engineer, Full-Stack Analytics

Altoros; Pasadena (TX); On-site; USD 140,000 - 210,000; Part time

Job summary

Altoros is staffing a Senior Support Engineer for a client engagement focused on an analytics platform. This is a full-stack and data-stack role: you own the platform shell, the ingestion and semantic layer, and a bounded amount of embedded analytics upkeep.

The engagement runs 80 hours per month with CT-aligned hours, starting in an observe-and-define phase and progressing toward outcome-based delivery from month two, including uptime targets and defect reduction.

Qualifications

• Hands-on AI-first delivery across the full development lifecycle.
• Full-stack experience with React/TypeScript and SSO/multi-tenant architecture.
• Dagster orchestration experience; strong DBT/SQL data transformation skills.
• Experience with BigQuery and the Google Cloud Platform data stack.
• Familiarity with semantic-layer tools (Cube) and embedded analytics tooling.
• Excellent stakeholder communication and Confluence documentation.

Responsibilities

• Maintain platform shell and authentication/SSO integration.
• Own data ingestion pipelines and Dagster orchestration.
• Develop semantic layer metrics and data modeling.
• Support embedded analytics components and theming.
• Document architecture and handover in Confluence.
• Deliver against defined outcomes from month two; uptime targets.

Skills

AI-first delivery

Full-stack development

React / TypeScript

SSO / multi-tenant auth

Dagster orchestration

DBT / SQL

BigQuery / GCP stack

Semantic layer tooling

Embedded analytics familiarity

Documentation in Confluence

Client stakeholder engagement

Tools

Dagster

dbt

SQL

BigQuery

GCP

Cube

React

TypeScript

Confluence

Embeddable SDK

Job description

Altoros is staffing a Senior Support Engineer for a client engagement focused on an analytics platform. This is a full-stack and data-stack role: you own the platform shell, the ingestion and semantic layer, and a bounded amount of embedded analytics upkeep.

The engagement runs 80 hours per month with CT-aligned hours, starting in an observe-and-define phase and progressing toward outcome-based delivery from month two, including uptime targets and defect reduction.