• Design and implement client-facing and internal APIs • Orchestrate data flows between backend systems • Create and manage database schemas • Build automated test suites • Lead the design and implementation of substantial product features end-to-end • Evaluate and integrate with third-party services and tools • Help to mentor mid-level and junior engineers on your team

• Analyze and optimize storage strategies for ML experiment data and metadata. • Design and implement intelligent retention and expiration for large-scale datasets. • Modernize and refactor ETL/ELT pipelines to improve scalability and ease of maintenance. • Create and populate additional schemas for validated and curated datasets. • Build or enhance database-backed applications supporting ML R&D and production analytics. • Collaborate with ML engineers, SREs, and platform teams. • Provide knowledge transfer for long-term maintainers.

• Build and expand our data pipelines and data products supporting Experimentation, Release observability, Metrics, Product Analytics and Flag Insights product lines, as well as internal Business Intelligence. • Collaborate with frontend engineers, product managers and UX designers to deliver user-facing features • Monitor and improve database and pipeline performance • Write unit, integration, and load tests as necessary • Actively participate in code reviews • Write and review technical proposals • Improve engineering standards, tooling, and processes

• Develop web applications across all layers • Interpret requirements and propose technical solutions • Write code following best practices, test, document, and deliver robust features • Actively participate in code reviews, estimations, and technical discussions