Database Engineer

Scale AI Scale AI · Data AI · San Francisco, CA · Horizontals EPD

Database Engineer role focused on building and scaling database foundations for Scale AI's platform, supporting distributed systems, data-intensive applications, and ML infrastructure. Responsibilities include collaborating with various teams, owning services, mentoring engineers, improving engineering standards, and working on data and security needs. Requires experience with database platforms, SQL optimization, distributed systems, and cloud platforms.

What you'd actually do

  1. Build and mature database foundations for Scale, leveraging industry-standard platforms.
  2. Collaborate with stakeholders across the organization, such as software developers, platform engineers, machine learning scientists, customer operations, etc.
  3. Own services or systems and define their long-term health goals, while also improving the health of surrounding components.
  4. Mentor other engineers and become deeply involved in architectural design and database best-practices.
  5. Improve our high engineering standards, tooling, and process.

Skills

Required

  • 5+ years of industry experience as a database engineer post graduation
  • Engineering experience with building real-time and distributed system architecture
  • Experience designing and self hosting databases on industry standard public cloud platforms
  • Deep familiarity with design, architecture, optimization, and tuning multiple database platforms such as MongoDB, Postgres, MySQL, DynamoDB, Redis
  • Deep familiarity with SQL query optimization, database indexing, scalability (partitioning/sharding), and replication
  • Experience developing and optimizing backup and restore functionality to meet RTO goals
  • Intermediate experience in at least one coding language: Typescript, Python, Go, Java, C++
  • Experience working with Docker, Kubernetes, and Infra-as-Code (e.g. Terraform)

Nice to have

  • Prior startup experience
  • Experience with AWS, Datadog, ElasticSearch
  • Experience with cloud-based data warehouse solutions like Snowflake or Databricks
  • Experience with cost optimization strategies and techniques for database platforms
  • Experience developing and designing intermediary data abstraction layers
  • Mentored and grown members of your team or been a tech lead on large projects
  • experience supporting GPU/ML workloads

What the JD emphasized

  • deep experience building and scaling both structured and unstructured database platforms
  • supporting distributed systems, data-intensive applications, and machine learning infrastructure
  • deep familiarity with design, architecture, optimization, and tuning multiple database platforms
  • Deep familiarity with SQL query optimization, database indexing, scalability (partitioning/sharding), and replication