Senior Data Platform Engineer – Large-Scale Storage

Scale; San Francisco (CA); Hybrid; USD 252,000 - 315,000; Full time

Benefits offered by this job

Equity-based compensation

Health/dental/vision coverage

Generous PTO

Learning & development stipend

Commuter stipend

Job summary

Scale is building AI-ready data platforms and RLHF-enabled systems. You will lead design, storage, streaming, and indexing foundations, collaborating across teams to deliver features and improve engineering practices.

The role combines technical leadership with hands-on implementation on large-scale data platforms. You will mentor others, shape standards, and work closely with stakeholders to align engineering decisions with business needs, including evolving cloud deployments and distributed

Qualifications

• 8+ years of full-time engineering experience, backend, with large-scale data storage/warehousing.
• Extensive experience in MongoDB, Postgres; streaming/processing (Kinesis, Flink, Spark).
• Knowledge of indexing/caching (ElasticSearch, Redis) and data query engines (Trino, Presto, Snowflake).
• Track record mentoring and leading teams on successful projects.
• Excellent communication and collaboration, able to translate tech to non-technical stakeholders.
• Experience with Kubernetes and public cloud deployments.
• Deep understanding of distributed systems and cloud/data platforms.

Responsibilities

• Drive architecture, design, implementation, and reliability of data platforms and systems.
• Collaborate with cross-functional teams to define and deliver new features.
• Identify opportunities to improve programming practices, processes, and tools.
• Present technical information to teams and stakeholders, providing guidance on development processes.
• Provide technical leadership, upholding and upleveling engineering standards, mentoring juniors.

Skills

Backend engineering

Distributed systems

Mentoring

Cross-functional collaboration

Communication

Cloud platforms

Kubernetes

Data storage & warehousing

Real-time streaming

Data indexing/caching

Tools

MongoDB

Postgres

Kinesis

Flink

Spark

ElasticSearch

Redis

Trino

Presto

Snowflake

Docker

Kubernetes

Public cloud

Job description

Scale is building AI-ready data platforms and RLHF-enabled systems. You will lead design, storage, streaming, and indexing foundations, collaborating across teams to deliver features and improve engineering practices.

The role combines technical leadership with hands-on implementation on large-scale data platforms. You will mentor others, shape standards, and work closely with stakeholders to align engineering decisions with business needs, including evolving cloud deployments and distributed