Data Platform Engineer - Scale & Resilience (Hybrid)

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

Benefits offered by this job

Hybrid work model

Equity options

Discretionary bonus

Job summary

Eightfold.ai's Data Platform team designs, develops, and maintains large-scale distributed systems powering millions of users. You will apply cutting-edge technologies to build resilient, scalable platforms that underpin our entire product suite.

This hybrid role in Santa Clara, CA offers a base salary range of $130,750–$181,000 USD, plus a discretionary bonus and pre-IPO equity. You will collaborate with Engineering, Operations, Analytics, Marketing and Business teams to deliver end-to-end data

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 core data platform architecture with auto-scaling and fault tolerance.
• Drive scaling, optimization, and performance of the Data Platform.
• Research and implement new data processing techniques in collaboration with stakeholders.
• Diagnose and resolve problems in distributed systems and support deployment across environments.
• Collaborate with Engineering, Operations, Analytics, Marketing and Business teams.
• Work across AWS and Azure cloud platforms.

Skills

AWS

Python

Flask

Distributed systems

Data pipelines

Data ingestion

Data integration

Job description

Eightfold.ai's Data Platform team designs, develops, and maintains large-scale distributed systems powering millions of users. You will apply cutting-edge technologies to build resilient, scalable platforms that underpin our entire product suite.

This hybrid role in Santa Clara, CA offers a base salary range of $130,750–$181,000 USD, plus a discretionary bonus and pre-IPO equity. You will collaborate with Engineering, Operations, Analytics, Marketing and Business teams to deliver end-to-end data