Senior Data Engineer, MLOps [Remote-US]

Quanata; United States; Remote; USD 213,000 - 300,000; Full time

Job summary

Join a leading company as a Senior Data Engineer, focusing on MLOps to enhance the machine learning lifecycle. Collaborate with data engineers and scientists to implement automation from data collection to model monitoring. Leverage AWS technologies and design scalable solutions to drive impact in the insurance industry. Enjoy competitive salary, benefits, and the flexibility of remote work.

Benefits

Medical, dental, vision, life insurance

401(k) Plan with company match

Virtual wellness allowance

Headspace app subscription

Up to $5000 for professional development each year

Four weeks of PTO in the first year

Work from Home Equipment stipend

Qualifications

• 8 years of industry experience with 2 years focused in MLOps.
• Experience with the end-to-end machine learning lifecycle.
• Excellent written and verbal communication.

Responsibilities

• Operationalize key data science solutions across underwriting, pricing, and claims.
• Design and build ML pipelines using AWS services.
• Monitor production models for performance and data quality.

Skills

Python

Docker

ML Governance

IaC (Infrastructure as Code)

AWS Step Functions

Bash

Bazel

Education

Bachelor degree or equivalent

Tools

AWS (SageMaker)

Snowflake

Terraform

CI/CD tools

Kafka

MLflow

Job description

To help keep everyone safe, we encourage all applicants to pay close attention to protect themselves during their job search. When applying for a position online you are at risk of being targeted by malicious actors looking for personal data. Please be aware we will only reach out via email using the domain quanata.com. Anything that does not match those domains should be ignored and considered a security risk.

About Us

Quanata is on a mission to help ensure a better world through context-based insurance solutions. We are an exceptional, customer centered team with a passion for creating innovative technologies, digital products, and brands. We blend some of the best Silicon Valley talent and cutting-edge thinking with the long-term backing of leading insurer, State Farm.

Learn more about us and our work at quanata.com

Our Team

From data scientists and actuaries to engineers, designers and marketers, we’re a world class team of tech-minded professionals from some of the best companies in Silicon Valley, and around the world. We’ve come together to create the context-based insurance solutions and experiences of the future. We know that the key to our success isn't just about nailing the technology—it’s hiring the talented people who will help us continue to make a quantifiable impact. The role

We’re looking for a Senior Data Engineer with a specialty in MLOps Engineering that can help drive the organization toward model development and delivery best practices. You will help shape and implement automation across the machine learning lifecycle from data collection to model training to model monitoring. In this high impact role, you will partner with both data engineers focused on data science service delivery and data scientists to develop a robust platform that shortens the time to market of new data science models at Quanata.

Your day-to-day

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.

About you

• Bachelor degree or equivalent relevant experience and;


• 8 years of industry experience with 2 years focused in 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 (e.g., automating model training, validation, and deployment)

Bonus points

• Experience in designing and developing large-scale distributed systems, complex APIs, or contributing significantly to platform-level software engineering projects.


• Proficiency in utilizing Snowflake's advanced capabilities for ML, such as Snowpark for Python/Java/Scala development, creating and managing user-defined functions (UDFs) for in-database scoring, or integrating directly with external model training and serving platforms.


• Prior experience working within the insurance industry or another highly regulated environment, demonstrating an understanding of pertinent regulatory, security, and data governance challenges.

Salary: $213,000 to $300,000*

*Please note that the final salary offered will be determined based on the selected candidate's skills, and experience, as well as the internal salary structure at Quanata. Our aim is to offer a competitive and equitable compensation package that reflects the candidate's expertise and contributions to our organization.

Additional Details:

• 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 and a 401(k) Plan with a company match.


• Work from Home Equipment : 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. Also, our teams work with MacBook Pros, which we will deliver to you fully provisioned prior to your first day.


• Paid Time Off: 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. The twelve weeks is applicable to both birthing and non-birthing parent.


• Personal and Professional Development: We’re committed to investing in and helping our people grow personally and professionally. All employees receive up to $5000 each year for professional learning, continuing education and career development. All team members also receive LinkedIn Learning subscriptions and access to multiple different coaching opportunities through BetterUp.


• Location : We are a remote-first company for most positions so you may work from anywhere you like in the U.S, excluding U.S. territories. For most positions,occasional travel may be requested or encouraged but is not required. Some positions might require travel per the job description provided to the employee.Employees based in the San Francisco Bay Area or in Providence, Rhode Island may commute to one of our local offices as desired.


• Hours : We maintain core meeting hours from 9AM - 2PM Pacific time for collaborating with team members across all time zones.

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.https://www.sf.gov/sites/https://www.sf.gov/sites/default/files/2022-12/FCO%20poster2020_0.pdf

This role is employed by Quanata, LLC which is a separate company in the State Farm family of companies.

If you require a reasonable accommodation, please reach out to your Talent Acquisition Partner for assistance.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Technology, Information and Internet

Referrals increase your chances of interviewing at Quanata by 2x

Sign in to set job alerts for “Senior Data Engineer” roles.

Data Architect – Databricks, ADF in Property and Casualty domain exp and guidewire

United States $94,800.00-$151,400.00 1 hour ago

Data Engineer Lead(SAP HANA, Databricks, Azure Data Factory, Delta Lake and PySpark)/Remote

Senior Electronic Data Interchange Analyst

New York, NY $153,000.00-$210,000.00 6 months ago

San Francisco, CA $153,000.00-$210,000.00 6 months ago

Lees Summit, MO $119,985.00-$169,135.00 5 days ago

United States $72,000.00-$148,500.00 5 days ago

Senior Workforce Management Data Analyst

United States $136,400.00-$178,300.00 4 days ago

United States $70,700.00-$106,100.00 23 hours ago

Senior Software Engineer (Consumer - Growth & App Infra, Growth Foundations)

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.