Our team is engaging Data Analysts to contribute expertise to a confidential client project focused on evaluating AI assistants in real-world analytical workflows leveraging cloud data warehouses. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
• Execute structured evaluation tasks simulating typical analytical workflows (e.g., anomaly investigation, KPI reporting, data refreshes) using AI-powered solutions with cloud data warehouse connectivity.
• Independently verify AI-generated figures against source data by writing and running your own SQL queries, and assess the correctness of data joins, filters, and time windows.
• Maintain, reset, and manage seeded datasets within Snowflake, ensuring data integrity and correct answer states for test scenarios.
• Oversee warehouse roles, permissions, and access controls to facilitate secure and repeatable evaluation environments.
• Configure and document connectivity and authentication processes across multiple analytics and SaaS platforms.
• Investigate and document novel or undocumented product behavior encountered during workflow execution.
• Participate in calibration sessions with peers to ensure consistency and rigor when grading or scoring outputs.
Preferred Qualifications
• At least 3 years of hands-on experience as a data analyst or analytics engineer, with advanced SQL skills and expertise in Snowflake (warehouses, access control, query history).
• Demonstrated proficiency in auditing and reconciling reported metrics against raw data, with a keen eye for catching subtle aggregation or logic errors.
• Familiarity with business and finance analytics, including KPI definitions and reporting practices relevant to leadership or external stakeholders.
• Experience in administering database access, managing roles, grants, and integrating authentication/security protocols; OAuth or security-integration familiarity is advantageous.
• Working knowledge of common SaaS tools such as Slack, Google Workspace, or Microsoft 365 for sharing analytical outcomes.
• Prior experience using AI assistants for analytics, with a critical perspective on the accuracy of AI-generated SQL and outputs.
• Background in rubric-based evaluation, QA, or data labeling, with a meticulous approach and strong written and verbal communication skills.
Skills mentioned
ReportingSQLSnowflakeQA
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