Published: Fri, 06 Jun 2025 20:50:29 GMT

Position: Senior Data Engineer – MLOps

Company: Quanata

Location: Remote (U.S. only)

Salary: $213,000 – $300,000 (final salary based on skills and experience)

Benefits: Medical, dental, vision, life insurance, supplemental income plans, Headspace app subscription, monthly wellness allowance, 401(k) plan with company match

Work from Home Equipment: One-time $2,000 payment for purchase of in-home office equipment and furniture, provided MacBook Pro for work

Paid Time Off: Four weeks of PTO in first year, 12 weeks of fully paid parental leave, up to $5,000 per year for professional development, LinkedIn Learning subscription, access to coaching opportunities through BetterUp

Hours: Core meeting hours from 9AM – 2PM Pacific time, occasional travel may be requested or encouraged but not required

About Us:

Quanata is a customer-centered team on a mission to create innovative technologies and digital products for context-based insurance solutions. We are a blend of Silicon Valley talent and the backing of leading insurer, State Farm.

Our Team:

We are a world-class team of tech-minded professionals, including data scientists, actuaries, engineers, designers, and marketers, with experience from top companies in Silicon Valley and around the world.

The Role:

We are seeking a Senior Data Engineer with expertise in MLOps Engineering to help drive our organization towards best practices in model development and delivery. You will play a key role in shaping and implementing automation across the machine learning lifecycle, from data collection to model training to model monitoring. This is a high-impact role where you will collaborate with data engineers and data scientists to develop a robust platform that accelerates the time to market for new data science models at Quanata.

Your Day-to-Day:

– Operationalize data science solutions for risk-prediction products in 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 and Snowflake.
– Manage a shared feature store (Snowflake Snowpark + Kafka) for batch and real-time feature retrieval.
– Own real-time inference services, including managing low-latency endpoints and deploying blue/green or canary deployments.
– Implement comprehensive testing strategies within robust CI/CD pipelines to maintain high platform quality.
– Enable ML Governance by managing model and data versioning, experiment tracking, and reproducibility.
– Implement event-driven orchestration for automated retraining, evaluation, and redeployment.
– Monitor production models for performance, drift, and data quality and drive automated remediation.

About You:

– Bachelor’s 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 skills 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.

Bonus Points:

– Experience in designing and developing large-scale distributed systems, complex APIs, or contributing to platform-level software engineering projects.
– Proficiency in utilizing Snowflake’s advanced capabilities for ML, such as Snowpark and creating and managing user-defined functions (UDFs).
– Prior experience in the insurance industry or another highly regulated environment, demonstrating an understanding of pertinent regulatory, security, and data governance challenges.

Additional Details:

– This role is employed by Quanata, LLC, which is a separate company in the State Farm family of companies.
– Quanata, LLC is an equal opportunity workplace. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status.
– Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. If you are a San Francisco resident, please read the City and County of San Francisco’s Fair Chance Ordinance notice.
– If you require a reasonable accommodation, please reach out to your Talent Acquisition Partner for assistance.

To Apply:

Please submit your application through our website at quanata.com/careers. Only applications submitted through our website will be considered. Thank you for your interest in joining our team at Quanata!
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