Senior Data Engineer, MLOps

🕒 December 10, 2025

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Quanata

WebsiteLinkedInAll Job Openings

201 - 500 employees

🤖 Artificial Intelligence

☁️ SaaS

Artificial Intelligence • Insurance • SaaS

Quanata is a company that empowers the insurers of tomorrow with AI-assisted modeling capabilities, real-time telematics solutions, and risk-based acquisition innovations, focusing on context-based insurance solutions. They provide advanced contextual and behavioral risk modeling, digital experiences, and telematics-driven rewards programs. Quanata is backed by industry leader State Farm and utilizes Silicon Valley talent and technology to drive innovation in the insurance sector. Their platform offers cloud-native technology solutions for insurers, including telematics-focused consumer-facing apps. Based in San Francisco, CA, Quanata aims to modernize claims processes and enhance underwriting and marketing capabilities for market-leading insurers and innovative insurtechs.

📋 Description

• Operationalize key data science solutions that enable risk‑prediction products across underwriting, pricing, claims routing, and marketing. • Design and build ML pipelines using industry best practices, primarily leveraging AWS services like SageMaker, and integrating with tools such as MLflow for experiment tracking and data platforms like Snowflake. • Stand‑up and operate a shared feature store (Snowflake Snowpark + Kafka) that supports both batch and real‑time feature retrieval. • Own real‑time inference services, exposing low‑latency endpoints (SageMaker endpoints or EKS micro‑services) and managing blue/green or canary deployments. • Implement comprehensive testing strategies (including Unit, integration, data validation, model validation, and performance testing) within robust CI/CD pipelines to maintain high platform quality. • Enable ML Governance: Manage ML models and data versioning, experiment tracking, and reproducibility. • Implement event‑driven orchestration that triggers automated retraining, evaluation, and redeployment based on data drift or business events. • Monitor production models for performance, drift, and data quality—and drive automated remediation.

🎯 Requirements

• Bachelor degree or equivalent relevant experience. • 8 years of industry experience with 2 years focused on MLOps and 2 years in software engineering or equivalent experience. • Comprehensive experience in Python and docker. • Familiarity with build tooling such as bash and bazel. • Advanced proficiency in IaC principles and tools like Terraform. • Demonstrated expertise in designing, deploying, and managing scalable and resilient MLOps solutions on AWS. • Applied expertise in the end-to-end machine learning lifecycle, including data ingestion, preprocessing, model training, deployment, and production monitoring. • Excellent written and verbal communication with a strong collaborative focus. • Proficiency in designing and implementing workflows using tools like AWS Step Functions. • Experience with CI/CD tailored for machine learning systems.

🏖️ Benefits

• We provide a wide variety of health, wellness and other benefits. • These include medical, dental, vision, life insurance and supplemental income plans for you and your dependents. • A Headspace app subscription. • Monthly wellness allowance. • A 401(k) Plan with a company match. • Given our virtual environment— in order to set you up for success at home, a one-time payment of $2K will be provided to cover the purchase of in-home office equipment and furniture at your discretion. • All employees accrue four weeks of PTO in their first year of employment. • New parents receive twelve weeks of fully paid parental leave which may be taken within one year after the birth and/or adoption of a child. • Each year for professional learning, continuing education and career development, we’re committed to investing in and helping our people grow personally and professionally. • All employees receive up to $5000.