Senior Data Engineer: Scalable Pipelines & Data Modeling

Unchain Data; Menlo Park (CA); On-site; USD 196,000 - 230,000; Full time

Benefits offered by this job

Health insurance

Equity ownership

401(k) matching

Paid time off

Mental health benefits

Office meals and events

Job summary

Robinhood is hiring a Senior Data Engineer in Menlo Park, CA. You will design and evolve core datasets and scalable data pipelines, ingesting events and database snapshots into our data lake.

You will collaborate with product, engineering, data science, and finance to ensure high-quality, well-modeled data for decision-making and product analytics. This role requires 5+ years of experience with end-to-end data pipelines, production Python, Spark/Flink, and strong SQL.

Qualifications

• 5+ years building end-to-end data pipelines.
• Hands-on software engineering with production-level Python.
• Experience with large-scale data pipelines using open source frameworks (Spark, Flink).
• Strong SQL skills (Presto, Spark SQL).
• Experience across the data stack (infrastructure, analytics, visualization).
• Able to democratize data through insights and solutions.

Responsibilities

• Define and build key datasets across Robinhood product areas.
• Build scalable data pipelines using Python, Spark and Airflow to move data into the data lake.
• Collaborate with upstream engineering to enhance data generation patterns.
• Work with data consumers to design intuitive data models.
• Contribute to data engineering tooling and standards.
• Promote data engineering best practices across the company.

Skills

Python

Spark

SQL

Data pipelines

Collaboration

Tools

Airflow

Flink

Job description

Robinhood is hiring a Senior Data Engineer in Menlo Park, CA. You will design and evolve core datasets and scalable data pipelines, ingesting events and database snapshots into our data lake.

You will collaborate with product, engineering, data science, and finance to ensure high-quality, well-modeled data for decision-making and product analytics. This role requires 5+ years of experience with end-to-end data pipelines, production Python, Spark/Flink, and strong SQL.