# Staff Software Engineer, Data Platform

**Company:** [Scale AI](https://hotfix.jobs/companies/scale-ai)
**Location:** San Francisco, CA, Seattle, WA, New York, NY
**Role:** Data Engineering
**Salary:** $248k – $311k/yr
**Experience:** 8+ years
**Skills:** MongoDB, Postgres, Kinesis, Flink, Spark, Elasticsearch, Redis, Trino, Presto, Snowflake
**Posted:** 2026-02-12

> Leads architecture and development of large-scale data platforms for AI, including storage, streaming, caching, and indexing. Requires 8+ years experience with databases, streaming tools, Kubernetes, and distributed systems.

## Job Description

## Responsibilities
- Drive the architecture, design, implementation, and reliability of foundational data platforms and systems, working closely with stakeholders.
- Collaborate with cross-functional teams to define, design, and deliver new features.
- Proactively identify opportunities for improvements to programming practices, processes, and tools.
- Present technical information to teams and stakeholders, providing guidance on development processes and technologies.
- Provide technical leadership, including upholding engineering standards and mentoring junior engineers.

## Requirements
- 8+ years of full-time engineering experience in back-end systems, specifically large-scale data storage, streaming, and warehousing.
- Extensive experience with database technologies (**MongoDB**, **Postgres**), streaming/processing (**Kinesis**, **Flink**, **Spark**), indexing/caching (**ElasticSearch**, **Redis**), and query engines (**Trino**, **Presto**, **Snowflake**).
- Track record of mentoring and leading teams in successful projects.
- Excellent communication and collaboration skills to translate complex technical concepts.
- Experience with containerization & deployment technologies like **Kubernetes** and public cloud offerings.
- Deep understanding of distributed systems, cloud platforms, and data systems.
- Experience driving cross-functional collaboration.

## Nice-to-Haves
- Strong knowledge of software engineering best practices and CI/CD tooling (**CircleCI**).
- Experience with performance tuning and cost optimizations of cloud-based data platforms.
- Experience defining data lifecycle strategy and tooling for data privacy (e.g., GDPR).
- Experience scaling products at hyper-growth startups.
- Excitement to work with AI technologies.

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