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Salary: USD 132,000 - 198,000 / annual
X.ai (SpaceXSI) is building Super Intelligence to help humanity understand the universe, developing the full stack from Colossus supercomputers to Grok models and applications. This Data Visualization Engineer role is a hands-on builder who owns how the organization turns data into decisions.
You will serve as the sole administrator of the BI platform (currently Tableau Server), managing upgrades, patches, maintenance, license management, SSO, and data drivers. You'll support 12 department sites and their Site Admins, plus approximately 700 users, owning key Slack channels and handling roughly 12 BI requests per week through Slack and Jira covering access, ownership changes, data source issues, troubleshooting, and bug fixes.
Key responsibilities include: rapidly designing and building dashboards and data products that transform complex data into clear, decision-ready insights; maintaining an inventory of existing reports and dashboards while working with business owners to decide what to migrate, rebuild, or retire; helping stakeholders select the right solution for each use case (dashboard, custom application, Grok team bot, etc.) and leading migrations; setting standards for data access, row-level security, and visualization quality; and proactively communicating with Site Admins, users, and developers about downtime, upgrades, and widespread issues.
You'll work at the intersection of data engineering, analytics, and product, partnering with the business to shape a modern, unified reporting and analytics solution.
REQUIREMENTS:
- Strong SQL, including complex joins, window functions, and performance tuning
- Data visualization and dashboard design expertise: chart selection, UX, and storytelling with data
- Row-level security and data access controls knowledge
- Rapid dashboard development in one or more BI tools (Tableau, Looker, Power BI, Superset, or similar)
- Platform administration fundamentals: SSO/SAML, APIs, and monitoring
- Comfort using AI tools to speed up analysis, development, and migrations
PREFERRED:
- Data modeling and warehouse concepts (star schemas, semantic layers) on platforms such as BigQuery, Snowflake, or Databricks
- Python or JavaScript for data prep, automation, or custom visuals
