Apache Superset Developer

Our AI-driven consumer intelligence platform processes 50+ billion data points monthly to deliver actionable consumer insights for global brands such as Coca-Cola, Unilever, and Bayer.

We're hiring an Apache Superset Developer to join our team.

The Role

Lead our migration from Power BI to Apache Superset and become the technical owner of how analytics dashboards get built at scale.

You'll architect a reusable component library, optimize performance against our Databricks lakehouse, and define standards that enable our team to ship faster, better dashboards.

What you'll do

• Migrate Power BI dashboards to Superset, improving performance from 8-12 second load times to under 3 seconds

• Build a parameterized chart library that other developers can reuse via Superset's API

• Optimize Superset + Databricks integration - get caching, semantic layers, and Delta Lake query patterns right

• Define dashboarding standards and Jinja templates for consistent, scalable development

• Collaborate across teams to turn business questions into dashboards that enterprise clients rely on

Required Qualifications

• 4+ years of BI/analytics/data visualization development
• 2+ years hands-on Apache Superset in production environments
• Strong SQL skills (window functions, CTEs, query optimization)
• Experience with Databricks/Spark SQL or similar lakehouse platforms
• Git workflow proficiency and collaborative development experience

Strong preference for:

• Superset deployment/operations experience (Docker, Kubernetes, Redis, Celery)
• Power BI fluency for accurate migration of existing dashboards
• Python proficiency for extending Superset APIs and integrations
• Jinja templating expertise in Superset contexts

What We Offer

• Fully remote role, with long-term growth opportunities
• You'll have real technical ownership as one of the first dedicated Superset experts. Your architectural decisions will power analytics for global enterprise brands, and performance improvements compound across hundreds of dashboards monthly.
• Work with modern tools (Databricks, Delta Lake, OpenAI) without legacy constraints.