Job Title: Senior Data Analyst Location: Remote (USA) | PST preferred; we are open to candidates located in other time zones. Hire Type: W2 Contract (12 Month) | (The client is only accepting USC/GC/GC-EAD candidates)

Summary

We are looking for a senior analyst to turn our data into trusted, accessible, AI-ready insight. You will own our Tableau analytics, build the governed data layer that dashboards and AI agents depend on, and deliver insights where teams already work, including Slack. You will partner closely with our data scientist, who owns data ingestion, Databricks pipelines, and machine learning, and with business leaders across sales, operations, finance, and customer success. Required Qualifications 10+ years of experience in analytics, business intelligence, or data science Advanced Tableau skills (dashboard design, data modeling, performance optimization) Strong SQL and data modeling skills Working proficiency in Python for automation, integrations, and analysis Comfort with version control, APIs, and reading and debugging code (generated or hand-written) Hands-on experience with AI tools (LLM APIs, prompt design, or agent workflows) and sound judgment about when their output cannot be trusted Ability to translate business questions into analytical solutions Excellent communication skills with both technical and executive audiences

Preferred Qualifications

Databricks (Databricks SQL, notebooks) or similar cloud data platforms Experience with tool-connection standards such as MCP Tableau Cloud, Tableau Pulse, or Tableau Next Slackbot, Slack workflows, or agent-building experience in Slack Experience with Salesforce, CRM analytics, or Customer 360 platforms Experience building evaluation or testing frameworks for AI outputs Familiarity with machine learning concepts and experience collaborating with data science teams Key Competencies Analytical Thinking: Solves business problems with data and catches errors others miss Data Storytelling: Turns insights into clear, actionable recommendations Technical Fluency: SQL, Python, Tableau, and modern data platforms AI Judgment: Builds and evaluates agents, and knows their limits Business Acumen: Aligns analytics to commercial outcomes Speed & Ownership: Ships working solutions quickly and iterates based on feedback Collaboration: Works effectively across data science, business teams, and executives