Opportunity at
RobinhoodSenior Software Engineer, Data Engineering
Robinhood is seeking a Senior Software Engineer, Data Engineering to design and develop foundational datasets and scalable infrastructure that drive decision-making across the company. This role…
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About This Role
Robinhood is seeking a Senior Software Engineer, Data Engineering to design and develop foundational datasets and scalable infrastructure that drive decision-making across the company. This role suits experienced engineering professionals who want to apply frontier technologies to major financial challenges. Robinhood operates as a financial services firm focused on democratizing finance, offering an environment where high-performing teams build products impacting product analytics, growth strategy, financial reporting, experimentation, and machine learning.…
Job Description
Robinhood is seeking a Senior Software Engineer, Data Engineering to design and develop foundational datasets and scalable infrastructure that drive decision-making across the company.
This role suits experienced engineering professionals who want to apply frontier technologies to major financial challenges. Robinhood operates as a financial services firm focused on democratizing finance, offering an environment where high-performing teams build products impacting product analytics, growth strategy, financial reporting, experimentation, and machine learning.
In this position, the engineer will construct reliable data systems, ingest application events and database snapshots into the data lake, and collaborate closely with product, engineering, data science, and finance departments. Responsibilities include shaping primary product datasets, developing Python and Spark data pipelines via Airflow, partnering with upstream engineering groups to refine data generation, and defining company-wide engineering standards.
The position is based out of the Menlo Park, California office, requiring in-person attendance at least three days per week.
Compensation and rewards include performance-driven bonuses, equity ownership, 401(k) matching, fully paid employee health insurance, lifestyle spending accounts, fertility and mental health services, and paid time off.
Responsibilities
- Develop and shape core datasets covering all product areas at Robinhood
- Build scalable data ingestion pipelines using Python, Spark, and Airflow
- Partner with upstream engineering teams to enhance data generation patterns
- Collaborate with data consumers to design intuitive and well-documented data models
- Contribute to shared data engineering tooling and establish organizational best practices
Requirements
- At least five years of professional background creating end-to-end data pipelines
- Hands-on software engineering capabilities to author production-grade Python code for user-facing applications or systems
- Expertise in constructing and managing large-scale data pipelines using open-source tools like Spark or Flink
- Strong SQL proficiency using Presto or Spark SQL
- Demonstrated ability to solve problems across infrastructure, analytics, and visualization platforms
Core Skills
Benefits
- Performance-driven compensation featuring multipliers, bonus programs, and equity ownership
- 401(k) matching
- 100 percent paid health insurance for employees with 90 percent coverage for dependents
- Lifestyle wallet for wellness and learning expenses
- Employer-paid life and disability insurance
- Fertility and mental health benefits
- Paid time off including holidays, sick leave, and parental leave
- Office amenities including catered meals and events
Frequently Asked Questions
What is the location and remote policy for this role?
This position is based in the Menlo Park, California office and requires employees to work in person at least three days per week.
What is the expected salary range for this position?
The expected base pay ranges from $196,000 to $230,000 USD for Zone 1 locations like Menlo Park, CA, with different ranges applicable for other zones.
What are the core technical requirements for applicants?
Candidates must have at least five years of experience building end-to-end data pipelines, production-level Python coding skills, expertise with open-source pipeline frameworks like Spark, and strong SQL abilities.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.