Remote Data Analyst - AI Evaluation (Cloud Data Warehouse Focus) at Henry Hire

micro1 is staffing a client project that stress tests AI assistants against the kind of analytical work real data teams do every day: pulling from cloud data warehouses, investigating anomalies, building KPI reports, and validating that AI-generated answers actually match the underlying data.

You won't be building AI. You'll be the domain expert who catches what it gets wrong. No AI background needed--what matters is that you know your way around SQL, Snowflake, and real analytics workflows well enough to spot a bad join or a mistimed aggregation on sight.

What You'll Actually Do

• Run realistic analytical scenarios Anomaly investigation, KPI reporting, and data refreshes using AI tools connected to live cloud data warehouses.

• Fact-check the AI. Write your own SQL against source data to verify every figure it produces, and scrutinize its joins, filters, and time windows for subtle errors.

• Own the test environment. Maintain, reset, and manage seeded datasets in Snowflake so each test scenario starts from a clean, correct state.

• Manage access. Set up and oversee warehouse roles, permissions, and access controls to keep evaluation environments secure and repeatable.

• Handle the plumbing. Configure and document authentication and connectivity across multiple analytics and SaaS platforms.

• Flag the weird stuff. Document any undocumented or unexpected product behavior you run into along the way.

• Calibrate with the team. Join peer sessions to keep grading and scoring consistent across evaluators.

What Gets You Hired

• 3+ years as a data analyst or analytics engineer with advanced SQL and real Snowflake experience--warehouses, access control, query history, not just SELECT statements.

• A sharp eye for reconciliation. You've audited reported metrics against raw data before and know exactly where aggregation logic tends to break.

• Business/finance analytics fluency. You understand how KPIs are defined and reported to leadership or external stakeholders, not just how to query them.

• Database administration chops. Managing roles, grants, and authentication protocols. Bonus points for OAuth or security-integration experience.

• Comfort with everyday SaaS tools. Slack, Google Workspace, or Microsoft 365 for sharing findings.

• Hands-on AI assistant experience for analytics. Ideally with a healthy skepticism toward AI-generated SQL and a track record of catching its mistakes.

• QA or rubric-based evaluation background. Data labeling, structured grading, or similar with meticulous attention to detail and strong written and verbal communication.