Data Engineer

Hebbia

📍San Francisco, CA
Posted May 19, 2026

Job Overview

Position

Data Engineer

Company

Hebbia

Location

San Francisco, CA

Work Type

On-site

Job ID

li-4416684880

Job Description

About Hebbia
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.

The Role
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.

Responsibilities

  • 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

Who You Are

  • 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

Compensation
The salary range for this position is set between $190,000 and $250,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

Life @ Hebbia
PTO:
Unlimited

Insurance:
Medical + Dental + Vision + 401K + Wellness Benefits

Eats:
Catered lunch daily + doordash dinner credit if you ever need to stay late

Parental leave policy:
3 months non-birthing parent, 4 months for birthing parent

Fertility benefits:
$15k lifetime benefit

New hire equity grant:
competitive equity package with unmatched upside potential

Interview Prep

AI-powered insights to help you prepare

Key Skills

Required:
Preferred:

Practice Questions

💡Technical Questions (3)
  • 1.How would you approach architecting and building a centralized data lake to consolidate disparate data sources for a platform like Matrix, ensuring it enables advanced analytics?
  • 2.Can you describe your experience using Airflow and DBT together to build and orchestrate ETL pipelines? How do you ensure data quality and reliability in this stack?
  • 3.Given the sensitive nature of financial data at Hebbia, how do you implement data governance, security, and compliance measures within your data pipelines?
🎯Behavioral Questions (3)
  • 1.As our first Data Engineer, you'll need to identify and own data projects end-to-end with a lot of autonomy. Tell me about a time you independently architected a data solution from scratch.
  • 2.This role requires close collaboration with product, engineering, and business teams to identify data gaps. Tell me about a time you worked with non-technical stakeholders to translate business requirements into a technical data solution.
  • 3.Hebbia operates in a high-growth, venture-backed startup environment where priorities shift rapidly. Describe a time you had to adapt your data engineering approach or pivot a project midway due to changing business needs.
🧩Situational Questions (2)
  • 1.You discover that a critical ETL pipeline feeding Hebbia's Matrix platform has been silently dropping records for the past week, impacting the accuracy of AI-driven analysis for clients. How do you handle this?
  • 2.You are tasked with consolidating data from various legacy sources into a new central data lake, but the business teams are pressuring you to deliver quick, ad-hoc reporting solutions before the lake is fully built. How do you balance these demands?

Resume Keywords

Make sure these keywords appear on your resume

ETL PipelinesData LakePythonSQLAirflowDBTData GovernanceSparkData WarehousingCross-functional Collaboration

Interested in this position? Apply directly on LinkedIn.

Apply on LinkedIn →