Data Analyst for AI Evaluation in Cloud Data Workflows
Overview
A remote contractor role focused on evaluating AI assistants within real-world analytical workflows that rely on cloud data warehouses. You’ll verify AI outputs against source data using SQL, manage seeded datasets in Snowflake, and help calibrate evaluation processes for consistency. The work supports training next‑generation AI systems, and your domain expertise matters even without prior AI experience. You will interact with secure access controls and maintain clear documentation of findings, configurations, and results. Snowflake and SQL are central to daily tasks, along with QA of analytics outputs.
What You'll Do7
- 1Execute structured evaluation tasks that mimic routine analytics, including anomaly checks, KPI reporting, and data refreshes, using AI-powered tools connected to a cloud data warehouse.
- 2Write and run your own SQL queries to verify AI figures against source data and assess joins, filters, and time window logic for accuracy.
- 3Manage seeded datasets in Snowflake, resetting and maintaining them to ensure reliable test scenarios and consistent answers.
- 4Oversee warehouse roles, permissions, and access controls to create repeatable and secure evaluation environments.
- 5Document connectivity and authentication setups across several analytics platforms and SaaS tools, ensuring traceable configurations.
- 6Investigate unusual or undocumented AI behavior encountered during workflow runs and report findings clearly.
- 7Collaborate with peers in calibration sessions to align scoring and maintain rigor in evaluating AI outputs.
Requirements4
- 1At least 3 years as a data analyst or analytics engineer with strong SQL abilities and hands-on Snowflake experience (warehouses, access control, query history).
- 2Proven skill in auditing metrics against raw data and spotting subtle errors in aggregation or logic.
- 3Experience using connectors to Claude and ChatGPT for analytics workflows.
- 4Familiarity with business and finance analytics, KPI definitions, and leadership-facing reporting practices.
Who Should Apply
The ideal candidate is a data professional with deep SQL and Snowflake know‑how who can independently verify AI-generated analytics against source data. This role suits someone who has worked with KPI reporting and understands access control, data governance, and securing analytics environments. It’s less suitable for those without solid Snowflake experience or those who haven’t audited metrics against raw datasets. Common fit gaps include limited SQL proficiency, lack of experience with Snowflake security features, or minimal exposure to KPI reporting for leadership audiences.
Salary Insight
$50 - $60/hr. Pay is discussed later in the process.
Location
Required Skills
Application Tip
Highlight your Snowflake and SQL credentials and include a concrete example of auditing a KPI against raw data, plus any experience with AI connectors for analytics.
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How your application is processed
1Application received
Your resume and details are logged the moment you apply.
2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
3Employer sees qualified profiles only
Only candidates who clear screening move forward.
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