Technical Business Analyst

ServiceNow•West Palm Beach, FL

40d

About The Position

Join our Sales Reporting and Analytics team to build practical, AI-powered utilities and light-weight agents that streamline analytics workflows and boost stakeholder productivity. You'll focus on Python and SQL scripting, ETL/data prep for tools like Snowflake and prototyping AI agents (Snowflake Cortex, LangChain, Databricks etc) that make it faster and easier for teams to access insights. Experience supporting Sales organization is a big plus.

Requirements

1-3 years professional experience (internships, co-ops, capstones count) in data/analytics engineering, ML/AI applications, or related fields.
Solid Python scripting skills (e.g., data model build using common libraries, API calls) and strong SQL
Exposure to AI agents/LLM apps through coursework, internships, hackathons, or personal projects
Familiarity with Snowflake or Snowflake (or similar BI/cloud data platforms).
Understanding of APIs/JSON/YAML, data structures, and software fundamentals.
Growth mindset, attention to detail, and ability to learn from feedback and iterate quickly.

Nice To Haves

Experience supporting Sales analytics or familiarity with sales concepts (pipeline, bookings, opportunities) and CRM tools.
Knowledge of semantic modeling (Snowflake, Power BI models, basic DAX) and techniques for LLM-friendly data restructuring.
Basic cloud familiarity (Azure/AWS/GCP) and workflow tools (e.g., schedulers/orchestrators).
Comfort explaining technical topics to non-technical partners and writing concise user docs.
If you have an experience of building a prototype of an AI agentic model, we would like to see a demo.

Responsibilities

Build and maintain scripts: Write clean, well-documented Python and SQL to ingest, transform, and validate data for Snowflake and Power BI datasets.
AI agent prototyping: Under mentorship, help design and prototype AI-powered tools that analyze data from multiple perspectives, uncover patterns, and deliver quicker, more actionable insights. These agents will assist with tasks such as exploring different angles of results, generating alternative views of metrics, and accelerating decision-making through automated analytics.
LLM-ready data prep: Convert enterprise data into LLM-optimized formats (semantic model, schemas, prompt-friendly outputs), ensuring reliability, basic guardrails, and reproducibility.
ETL + quality checks: Contribute to simple ETL pipelines, unit tests, data quality checks, and runbooks; assist in monitoring scheduled jobs and triaging issues.
Partner closely with the Data Technology org to ensure all AI agent work aligns with our AI Agent Build Framework - following approved workflow so the AI agents stay on the right path from day one. Participate in design reviews, reuse shared components, and provide feedback that helps streamline the framework.

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