Senior SDET – Data [Remote-US]

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 Quanata, LLC is an insurance technology innovation company that engineers advanced risk prediction and prevention solutions, develops risk-focused acquisition capabilities, and builds/supports a full-stack, flexible, digital & increasingly AI-native insurance platform. This helps our primary clients, State Farm and HiRoad Assurance Company, adapt to evolving market needs. Quanata, LLC is wholly owned and funded by State Farm. As a company that prioritizes an inclusive and positive culture, we believe the core of our success is in hiring talented people — across disciplines — who want to help us make a quantifiable impact. The Role Join our Data Platform QA team as a hands-on engineer focused on ensuring the quality, reliability, and performance of complex data platforms and machine learning workflows. In this individual contributor role, you’ll design scalable approaches to automated testing and quality assurance across data and ML systems. You’ll partner closely with Data Engineers, ML Engineers, Data Scientists, and DevOps teams to identify risks early, strengthen quality throughout the development lifecycle, and ensure data and model outputs can be trusted. You’ll also help shape testing practices across teams, troubleshoot complex production issues, and mentor other quality engineers while remaining actively involved in hands-on engineering. Your Day-to-Day Design and implement scalable automated testing frameworks for complex data pipelines, processing workflows, and machine learning models. Develop comprehensive testing strategies that address data quality, schema integrity, data drift, model accuracy, bias, and regression. Validate large-scale distributed data systems for accuracy, reliability, performance, and resilience. Partner across engineering, data science, and operations teams to embed quality throughout the software development and delivery lifecycle. Conduct exploratory testing to identify edge cases and risks in new features, data outputs, and machine learning workflows. Build continuous validation into automated development and deployment processes. Investigate production data and model failures, identify root causes, and help drive effective resolutions. Mentor junior SDETs and contribute to broader testing strategies, standards, and quality engineering best practices. About You Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or an equivalent combination of education and relevant experience. Typically 6–8 years of software testing experience, including at least 3 years focused on data platform or machine learning testing. Strong programming skills with experience building and maintaining automated testing frameworks. Hands-on experience testing complex data platforms, pipelines, and distributed data processing systems. Strong understanding of data validation approaches, including data quality, integrity, consistency, and schema validation. Understanding of machine learning concepts, workflows, and model evaluation methods. Experience developing automated validation approaches for data and machine learning systems. Deep understanding of continuous integration, continuous delivery, and infrastructure automation practices. Ability to troubleshoot complex data and model failures and contribute effectively to root cause analysis. Ability to collaborate effectively across engineering, data science, and operations teams. Strong analytical and problem-solving skills, with the ability to identify risks and edge cases in complex systems. Ability to mentor other quality engineers and contribute to shared testing standards and best practices. Bonus Points Experience evaluating machine learning models for interpretability, fairness, and bias. Familiarity with machine learning operations and model lifecycle practices. Experience monitoring the health and performance of production data pipelines and machine learning systems. Knowledge of data governance and compliance practices. Salary: $198,000 to $281,000 *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