Gen AI Data Quality Analyst

Responsibilities

• Conduct comprehensive data profiling on all source systems (e.g., Snowflake, Foundry, Excel) to identify data characteristics and anomalies.
• Identify, analyze, and document patterns, inconsistencies, and rule violations within datasets.
• Work closely with development and data quality teams to define, refine, and validate data rules.
• Hands‑on experience or strong familiarity with Gen‑AI tool chains (OpenAI, Azure OpenAI, Hugging Face, etc.), and cloud‑native data platforms (Databricks, Snowflake, etc.).
• Raise, track, and manage data issues that could impact application trust, scalability, or downstream processing.
• Provide continuous feedback loops to the development team during the development lifecycle, surfacing defects early.
• Collaborate with various Data Offices and Data Quality (DQ) teams to understand and apply existing business rules.
• Ensure the consistency and integrity of data quality practices.
• Contribute to long‑term efforts in improving data quality and integrity across all systems.

• Proven experience working with large datasets in platforms like Microsoft Excel, Snowflake, and Palantir Foundry.
• Strong analytical mindset and an exceptional attention to detail.
• Experience and proficiency in writing SQL and Python.
• The ability to "rip into a spreadsheet" to surface insights and discrepancies.
• Experience in data profiling or data quality analysis.
• Experience writing data quality rules.
  
  Comfortable working cross‑functionally with developers, product leaders, and business users.

• Insurance Industry knowledge
• Experience working as part of agile teams.
• Curious and persistent in finding the "why" behind data inconsistencies.
• A self-starter who enjoys solving data puzzles and embraces new challenges.
• Capable of ramping up quickly on new systems and business domains.
• Interested in making a strategic, long-term impact on the company's data assets.

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