Design, build, and scale the data that power our machine learning ecosystem – enabling consistent, reliable, and real-time access to features across development, training, and production environments
Job Summary
Design, build, and scale the data that power our machine learning ecosystem – enabling consistent, reliable, and real-time access to features across development, training, and production environments.
Implement and maintain scalable features serving offline (batch), online (real-time), and streaming ML use cases.
Define and enforce governance standards for feature registration, metadata management, lineage tracking, and versioning to ensure data consistency and reusability.
Matching Summary
Design, build, and scale the data that power our machine learning ecosystem – enabling consistent, reliable, and real-time access to features across development, training, and production environments.
Salary
Base: $117,200 - $223,900 annually; Bonus/Equity: Not specified; Benefits: Not specified
Skills & Requirements
Must-have
Python proficiency
Distributed data frameworks
Feature store technologies
Cloud data warehouse
Streaming data platforms
Cloud environments (AWS preferred)
CI/CD automation
Nice-to-have
Salesforce Ecosystem experience
Context engineering
RAG pipelines
Key Requirements
5+ years of experience in data engineering
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field
Experience with feature store technologies
Experience with cloud data warehouse and transformation framework
Expertise in streaming data platforms
Experience with cloud environments and infrastructure-as-code tools
Strong understanding of CI/CD automation, containerization, and API-driven integration patterns