Description

You will own the Databot agentic data query tool, stabilizing and extending its capabilities with new data sources and use cases. You will build production-grade internal data tools by translating stakeholder requirements into robust pipelines, semantic layers, and consumption interfaces. You will evaluate internal tools for potential external productization, ensuring they meet deployment standards including containerization and Kubernetes readiness. You will lead discovery sessions with business owners to align data access needs with engineering delivery.

This role is remote.

Responsibilities

• Maintain, stabilize, and enhance the Python-based Databot tool with peer collaboration.
• Design and implement data pipelines, semantic layers, and BI consumption interfaces.
• Containerize tools and prepare them for Kubernetes deployment and monitoring.
• Translate non-technical business requirements into clear data product specifications.
• Provide regular roadmap updates to engineering leadership.

Required Skills

• 5+ years of professional experience with Python as the primary development language.
• Strong proficiency with Docker for containerization and Kubernetes for deployment.
• Experience with Shell scripting for utility automation.
• Hands-on experience with BigQuery or equivalent cloud data warehouses.
• Ability to curate, wrangle, and build data-driven outputs from raw data.
• Proven track record of shipping internal tools that address ambiguous stakeholder needs.
• US timezone availability for internal collaboration.

Preferred Skills

• Experience with LLM-based agentic data consumption, MCP, or Google Cloud AI (Vertex AI, Gemini).
• Background in data lake architecture or data federation across heterogeneous sources.

Key Skills

Education

Bachelor's degree