Senior SDET

The role

We’re looking for an accomplished and well-rounded Senior SDET with strong experience in testing complex Data Platforms and validating Machine Learning workflows. This role requires a hands-on engineer who can build robust automated test frameworks, work closely with data scientists and engineers, and ensure the reliability, accuracy, and performance of our data-driven systems.

Your day-to-day

1. Design and implement scalable test automation frameworks for data pipelines, ETL workflows, and ML models.
2. Validate large-scale distributed data processing systems (e.g., Step Function, Kafka, Airflow, Snowflake, Databricks).
3. Develop testing strategies for data quality, schema validation, data drift, model accuracy, bias, and regression in ML pipelines.
4. Collaborate with Data Engineers, ML Engineers, and DevOps teams to embed quality throughout the CI/CD lifecycle.
5. Conduct exploratory testing on new features and data/ML outputs to catch edge cases and anomalies.
6. Integrate automated tests into the CI/CD pipeline for continuous validation.
7. Monitor and analyze production issues and help with root cause analysis for data and model failures.
8. Mentor junior SDETs and contribute to test strategy and quality best practices across teams.

About You

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field — or equivalent relevant experience.
• 6+ years of experience in software testing, including 3+ years focused on data platform or machine learning systems.
• Proficiency in a modern programming language commonly used for testing and automation.
• Experience developing and executing automated tests for data pipelines and large-scale data processing environments.
• Strong understanding of machine learning workflows, including model training, validation, and performance evaluation.
• Familiarity with data validation, transformation testing, and quality assurance frameworks.
• Knowledge of continuous integration and deployment practices, including automated testing and infrastructure management.
• Experience working in notebook-based development environments for data science or ML experimentation.

Bonus Points

• Experience evaluating model performance, interpretability, and fairness.
• Understanding of ML operations (MLOps) concepts, including model versioning, deployment, and lifecycle management.
• Exposure to monitoring and observability practices for data pipelines or ML systems.
• Knowledge of data governance, compliance, and responsible AI practices.

Salary: $185,000 to $265,000*

*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.