Senior Data Engineer: Scalable Pipelines & Data Modeling

Robinhood; California (MO); On-site; USD 172,000 - 230,000; Full time

Benefits offered by this job

100% paid health insurance

Dependent coverage 90%

Equity ownership

401(k) matching

Flexible benefits wallet

Life & disability insurance

Parental leave

Catered meals & events

Job summary

Robinhood is seeking a Senior Data Engineer in Menlo Park, CA to design, build, and evolve core datasets that power product analytics and company-wide metrics. You will ingest events and snapshots into the data lake and collaborate with engineers to improve data generation patterns and data models.

You will partner with analytics teams to deliver well-documented data models and scalable pipelines, shaping the technical foundation for data-driven decisions across the organization.

Qualifications

• 5+ years of experience building end-to-end data pipelines.
• Hands-on production-grade Python development.
• Experience with Spark, Flink, and open-source data frameworks.
• Strong SQL skills (Presto, Spark SQL).
• Experience solving problems across the data stack (infrastructure to analytics).
• Collaborative ability to democratize data through insights and solutions.

Responsibilities

• Define and build key datasets across Robinhood product areas. Lead the evolution of these datasets as use cases grow.
• Build scalable data pipelines using Python, Spark and Airflow to move data into our data lake.
• Partner with upstream engineering teams to enhance data generation patterns.
• Collaborate with data consumers across Robinhood to understand consumption patterns and design data models.
• Ideate and contribute to shared data engineering tooling and standards.
• Define and promote data engineering best practices across the company.

Skills

End-to-end data pipelines

Python production code

Spark & Flink

SQL (Presto, Spark SQL)

Data infrastructure

Collaborative data democratization

Job description

Robinhood is seeking a Senior Data Engineer in Menlo Park, CA to design, build, and evolve core datasets that power product analytics and company-wide metrics. You will ingest events and snapshots into the data lake and collaborate with engineers to improve data generation patterns and data models.

You will partner with analytics teams to deliver well-documented data models and scalable pipelines, shaping the technical foundation for data-driven decisions across the organization.