Senior Software Engineer, Data Compute

Robinhood

Hybrid

Quick summary

Work type: Hybrid
Location: Bellevue, WA
Salary: $196,000–$230,000 / yr
Posted: 1 day ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k

This role $213k

$171k most similar roles pay here $243k

This role pays more than 60% of similar roles. Most pay $177,900–$235,812 — the shaded band above. At the midpoint, this role pays about $213k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Robinhood

Robinhood is a financial technology company offering commission-free stock, ETF, options, and cryptocurrency trading through its mobile app, aimed at democratizing access to financial markets. Industry: Financial Technology & Investment App

Robinhood currently has 81 open roles on FindRole.

Listed pay typically runs $187,000–$220,000 across 80 roles with salary data.

Most-posted roles

View all roles at Robinhood

At a glance

TL;DR · Senior Software Engineer, Data Compute

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As a Senior Software Engineer on the Data Compute team at Robinhood, you will play a pivotal role in managing and evolving the company’s large-scale Spark and Airflow environments. Your responsibilities include designing scalable infrastructure to support millions of daily jobs and leading the migration of workloads to Databricks and Delta Lake architectures. You’ll collaborate with internal teams to optimize resource utilization and improve platform reliability through advanced metadata management and access controls using Unity Catalog and Trino. The ideal candidate has extensive experience with large-scale Spark, Databricks, Airflow, and lakehouse fundamentals such as S3-based data lakes and Delta Lake, along with expertise in query infrastructure like Trino or Hive Metastore. This role offers the opportunity to shape the next generation of data processing at a rapidly growing financial technology company.

Skills

Spark Databricks Airflow Delta Lake Unity Catalog Trino S3 Parquet CI/CD Python AWS Kubernetes

What you'll do

Design and build scalable platform primitives for Spark and Airflow to support global data infrastructure.
Lead migration of Spark workloads to serverless Databricks and Delta Lake architectures.
Optimize compute resource utilization and efficiency in large-scale distributed systems.
Implement advanced metadata management and access controls via Unity Catalog and Trino.
Collaborate with internal teams to deliver a seamless, self-serve data processing experience.

What we're looking for

Extensive experience with large-scale Spark and Databricks platforms.
Deep expertise in data orchestration using Airflow for complex job management.
Proven track record with lakehouse fundamentals, including Delta Lake and Parquet.
Familiarity with query infrastructure such as Trino and Hive Metastore.
Ability to optimize compute resources and manage costs in distributed systems.

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