Senior SDET, Data QA [Remote-US]

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.

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.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field OR equivalent relevant experience and;
• Typically requires 6 - 8 years of experience in software testing, to include 3 or more years in data platform or ML testing.
• Strong Python skills and experience with testing frameworks (e.g., PyTest, unittest).
• Hands-on experience with data technologies like SQL, Step Function, Kafka, Airflow, Snowflake, Data Lake, or similar.
• Understanding of machine learning concepts, pipelines, and evaluation metrics.
• Experience with tools like dbt tests, or custom validation frameworks.
• Deep knowledge of CI/CD and infrastructure-as-code (e.g., Jenkins, GitHub Actions, Terraform)
• Experience working with Sagemaker Notebook 

• Experience with model interpretability, fairness, and bias testing.
• Familiarity with MLOps platforms like MLflow, SageMaker, or Vertex AI.
• Exposure to monitoring tools like Prometheus, Grafana, or DataDog for data pipelines.
• Knowledge of data governance and compliance 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.