Member of Technical Staff | Data Engineering, Finance

The role

You will build reliable autonomous AI agents that detect and resolve complex financial data issues. You will build scalable pipelines to integrate new financial datasets and ensure consistency across sources.

What you will do

• Build reliable autonomous agents that detect, investigate and resolve financial data errors
• Tackle point-in-time accuracy, survivorship bias and other challenges
• Investigate and resolve complex data integrity issues
• Build scalable pipelines to integrate new financial datasets

Required qualifications

• Deep, hands-on experience building production data pipelines
• Experience working with financial data at a quantitative investment firm, data provider or similar environment
• Experience with Bloomberg, S&P Capital IQ, FactSet, LSEG/Refinitiv, MSCI Barra, or similar data providers
• Experience tackling complex financial data issues involving corporate actions, security mapping and point-in-time accuracy
• Ability to independently troubleshoot complex data issues
• Ability to work with vendors when needed
• Experience building AI agents or excitement to develop autonomous systems

Nice to have

• Experience with Snowflake, Databricks, Airflow, AWS, or related technologies

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• Catered lunches
• Commuter benefits
• Relocation allowance

Before you apply

• Current legal authorization to work in the US required
• Continuing work visa sponsorship available for full-time employees

About the company

Poesis is an AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. The founders managed institutional capital at Capital Group and led enterprise ML at Goldman Sachs and Amazon.