Data Engineer

The AI platform for investors and bankers that generates alpha and drives upside.

Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for BlackRock, KKR, Carlyle, Centerview, and 40% of the world’s largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally.

We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets.

Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership.

We are seeking our first Data Engineer, someone who can refine our data infrastructure, drive best practices for building data pipelines, and collaborate closely with both engineering and business teams to ensure every data need is met. If you are a self-starter with a proven track record of architecting end-to-end data solutions, we’d love to hear from you.

• →Architect, build, and maintain ETL pipelines and workflows that ensure high data quality and reliability
• →Design and manage a central data lake to consolidate data from various sources, enabling advanced analytics and reporting
• →Collaborate with cross-functional stakeholders (product, engineering, and business) to identify data gaps and develop effective solutions
• →Implement best practices in data security and governance to ensure compliance and trustworthiness
• →Evaluate and integrate new technologies, tools, and approaches to optimize data processes and architectures
• →Continuously monitor, troubleshoot, and improve data pipelines and infrastructure for performance, scalability, and cost-efficiency

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field
• 5+ years software development experience at a venture-backed startup or top technology firm, with a focus on data engineering
• Significant hands-on experience in data engineering (ETL development, data warehousing, data lake management, etc.)
• Adept at identifying and owning data projects end to end, with the ability to work independently and exercise sound judgment
• Proficient in Python and SQL; comfortable working with cloud-based data stack tools
• Familiar with big data processing frameworks (e.g., Spark, Hadoop) and data integration technologies (e.g., Airflow, DBT, or similar)
• Experience implementing data governance, security, and compliance measures
• Strong collaboration and communication skills, with the ability to translate business requirements into technical solutions
• Prior experience in a high-growth or startup environment is a plus
• You are comfortable working in-person 5 days a week

#LI-Onsite