Data Platform Engineer – Scalable Distributed Systems

Eightfold AI; Santa Clara (CA); Hybrid; USD 131,000 - 181,000; Full time

Benefits offered by this job

Hybrid work model

Equity awards

Discretionary bonuses

Job summary

Eightfold AI is hiring for a Senior Data Platform Engineer to design, develop, and maintain large-scale data platforms used by millions of users. You will lead architecture decisions for distributed, resilient systems and drive performance improvements across high-volume data pipelines.

You will collaborate with cross-functional teams and work across AWS and Azure, delivering end-to-end product capabilities with ownership and quality code.

Qualifications

• 2-6 years of professional experience in building core features of highly scalable data platform.
• Proven experience in building highly available distributed systems.
• Working experience in high-volume data pipelines, data ingestion and data integration.

Responsibilities

• Lead the design and evolution of the core data platform architecture with auto-scaling and fault tolerance.
• Drive scaling, optimization, and innovation of the Data Platform.
• Extend platform capabilities with new data processing techniques and collaborate with stakeholders.
• Diagnose and resolve complex problems in distributed systems and support deployment across environments.
• Partner with Engineering, Operations, Analytics, Marketing, and Business teams for end-to-end delivery.
• Work across AWS and Azure cloud platforms.

Skills

Distributed systems

Python

Flask

Performance optimization

Cloud platforms

Education

Bachelor's degree in Computer Science or related field

Tools

Flask Framework

AWS

Azure

GCP

Job description

Eightfold AI is hiring for a Senior Data Platform Engineer to design, develop, and maintain large-scale data platforms used by millions of users. You will lead architecture decisions for distributed, resilient systems and drive performance improvements across high-volume data pipelines.

You will collaborate with cross-functional teams and work across AWS and Azure, delivering end-to-end product capabilities with ownership and quality code.