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