Staff Data Engineer, AI-Driven Finance Platforms

Poesis AI; Menlo Park (CA); Ibrido; USD 160.000 - 250.000; Tempo pieno

Vantaggi offerti da questo lavoro

Relocation allowance

Catered lunches

Commuter benefits

Descrizione del lavoro

Poesis is building an AI-native investment firm where data quality directly shapes what our models learn and the decisions they make. As a Member of Technical Staff focused on data engineering, you'll build reliable autonomous AI agents that detect and resolve complex data issues and strengthen the foundation of our investment process.

This is an opportunity to pioneer a new approach to financial data engineering, with AI at the core of how data systems are built and operated.

Competenze

• Deep, hands-on experience building production data pipelines and working with financial data.
• Experience with Bloomberg, S&P Capital IQ, FactSet, LSEG/Refinitiv, MSCI Barra, or similar data providers.
• Tackled complex financial data issues involving corporate actions, security mapping and point-in-time accuracy.
• Able to independently troubleshoot complex data issues, work with vendors, and develop practical solutions.
• You've built AI agents or are excited to develop autonomous systems.

Mansioni

• Build autonomous agents to detect and resolve financial data errors, escalated to humans when needed.
• Address point-in-time accuracy and survivorship bias affecting financial models.
• Investigate data integrity issues, incl. conflicting prices, corporate actions, and security identifiers.
• Build scalable pipelines to integrate new financial datasets and ensure consistency across sources.

Conoscenze

Data pipelines

Financial data

Data vendors

Troubleshooting

Autonomous systems

Strumenti

Snowflake

Databricks

Airflow

AWS

Descrizione del lavoro

Poesis is building an AI-native investment firm where data quality directly shapes what our models learn and the decisions they make. As a Member of Technical Staff focused on data engineering, you'll build reliable autonomous AI agents that detect and resolve complex data issues and strengthen the foundation of our investment process.

This is an opportunity to pioneer a new approach to financial data engineering, with AI at the core of how data systems are built and operated.